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RTL Intern
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary As an RTL Intern at Etched, you will help design microarchitecture and implement logic in verilog. You will work with cutting-edge machine learning architectures, contribute to RTL block development, and participate in the full design cycle—from microarchitecture discussions to synthesis and timing feedback. You do not necessarily need prior ML/AI hardware experience; just the ability to learn quickly in a fast-paced, high-autonomy environment. We are looking for Fall '26, Spring '27, and Summer '27 interns. You may be a good fit if you have - Progress towards a Bachelor’s, Master’s, or PhD degree in electrical engineering, computer engineering, or a related field. - Familiarity with high-speed digital logic - Exposure to ASIC or SoC design concepts - Familiarity with SystemVerilog, UVM, or Python - Familiarity with verification work and writing test benches - Familiarity with physical design flows and tooling - Are able to learn quickly about transformers and other aspects of modern artificial intelligence Strong candidates may also have experience with - Familiarity with modern ML and LLM model architectures - Familiarity with numerical representations and functions - Familiarity with clocking and reset schemes - Ability to program with Python or another scripting language We encourage you to apply even if you do not believe you meet every single qualification. Program details - 12-week paid internship - Generous housing support for those relocating - Daily lunch and dinner in our office - Based at our office in San Jose, CA - Direct mentorship from industry leaders and world-class engineers - Opportunity to work on one of the most important problems of our time For any questions, contact internships@etched.com How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Performance Modeling Engineer
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Key responsibilities - Develop comprehensive performance models and projections for our architecture across varying workloads and configurations - Profile and analyze deep learning workloads on our hardware to identify micro-architectural bottlenecks and influence optimization opportunities - Drive hardware/software co-optimization by identifying where architectural features can unlock performance improvements - Run regressions and validate performance models against real systems and silicon - Inform next-generation architectural decisions by pathfinding across system and silicon options during design, proof-of-concept, and architecting phases You may be a good fit if you have at least one of the following: - Strong performance modeling and analysis skills with experience building analytical-based or simulation-based performance models - Solid understanding of computer architecture and micro-architecture, particularly for accelerators - Experience profiling and analyzing deep learning workloads on hardware accelerators (GPUs, TPUs, ASICs, FPGAs, or others) - Solid software engineering fundamentals with an eye toward auditability and maintainability Strong candidates may also have - Deep knowledge of GPU architectures and/or programming models like CUDA - Experience mapping models to multi-chip inference systems - Familiarity with transformer model architectures and inference serving optimizations - Experience with architecture simulators and performance modeling tools (gem5, trace-driven simulators, custom models) - Exposure to ASIC, FPGA, or CGRA-based accelerator development and hardware/software co-design principles - Published research in computer architecture, ML systems, or hardware acceleration Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2.5k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch + dinner in our office - Unlimited compute budget subject to ROI justification How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Advanced Packaging SI/PI Engineer
About Etched Etched is building hardware for frontier intelligence. We co-design chips, racks, software, and manufacturing to deliver best-in-class throughput and latency across both prefill and decode workloads. Our first products are heavily focused on inference. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history. Job Summary As a Signal & Power Integrity Engineer you will be responsible for the electrical performance of our AI accelerator platform across silicon, package, and board. The ideal candidate will have extensive experience with high-power package and board designs, robust power delivery networks, and high-speed signaling solutions in advanced packaging. You will work closely with silicon, package, platform, and system teams to co-design world-class platforms with OSAT and ODM partners. Intense focus on pushing what is possible in power delivery and high-speed signaling for our silicon. Key Responsibilities - SI/PI analysis of designs and optimization within 2D/2.5D/3D packages - Close interaction with Package Layout Designers, ASIC PD and IP teams as well as Board Schematic/Layout/SI/PI teams to optimize the best electrical performance - Drive SI requirements into interposer/substrate layout (high-speed routing: 112G/224G) from preliminary design through tape-out. - Drive PDN design and decoupling strategy across substrate and interposer, owning DC IR drop, dynamic IR drop, and impedance targets across all rails. - Own ball map / C4 / BGA pin assignment from soft freeze through final freeze in partnership with package layout, ASIC PD, and board layout teams. - Support board-level SI/PI and rack-level scale-up topology studies, including rack test vehicle design and cable characterization. - Participating in cross-functional meetings and design reviews. You may be a good fit if you have (Must-have qualifications) - Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, or a related field with a strong understanding of signal integrity and power integrity concepts and fundamentals. - 8+ years of SI/PI experience on high-performance ASIC, processor, or accelerator platforms. - Proven experience defining and closing PDN for high-power silicon, including substrate and PCB plane design, decap strategy, and dynamic IR/EM analysis. - Experience with developing systems with high-speed interfaces like HBM, SerDes and D2D interfaces. - Hands-on expertise with one or more of: ANSYS HFSS / SIwave, Cadence Sigrity (PowerSI / PowerDC), Keysight ADS. - Experience with CoWoS or equivalent advanced packaging materials and technologies including interposer SI/PI implications, C4 bump planning, and substrate stack-up trade-offs. - Track record of designing and correlating SI/PI test vehicles against silicon measurement during bring-up and lab characterization. - Strong analytical and communication skills, comfortable presenting risk, sign-off status, and trade-offs to cross-functional leadership. - Deeply creative and able to think from first principles. Strong candidates may also have experience with (Nice-to-have qualifications) - Familiarity with full RTL-to-GDSII context and how PD decisions interact with package and board PDN. - Experience with multi-die, 2.5D, or 3D packaging signoff, including chip-package-system (CPS) co-design. - Project management experience coordinating across internal teams, OSAT partners, and PCB ODMs. - Familiarity with modern ML and LLM model architectures, accelerator architectures, or HPC system design. - Startup experience or comfort working in fast-paced environments. Benefits - Medical, dental, and vision packages with generous premium coverage - $500 per month credit for waiving medical benefits - Housing subsidy of $2.5k per month for those living within walking distance of the office - Relocation support for those moving to San Jose (Santana Row) - Various wellness benefits covering fitness, mental health, and more - Daily lunch and dinner in our office - Unlimited compute budget subject to ROI justification How we’re different Etched believes in the Bitter Lesson http://www.incompleteideas.net/IncIdeas/BitterLesson.html. We are the first inference-focused frontier AI system, betting early on transformer and transformer-like architectures and on increasing model sizes. Our addressable market is the entirety of inference, unlike many of our competitors. We are a fully in-person team in San Jose (Santana Row), and greatly value engineering skills. We do not have boundaries between engineering and research, and we expect all of our technical staff to contribute to both and work across disciplines as needed.
Founding Product Marketing Lead
ABOUT E2B E2B is a fast-growing Series A startup with over $37M in funding and 8-figure revenue. We are building the Agent Cloud and power the infrastructure behind AI labs and some of the most widely used consumer and enterprise agents, including Manus, Genspark, Lindy, Groq, and Artificial Analysis. Our team includes original authors of Firecracker, the AWS microVM technology powering Lambda, along with alumni of Cognition, JetBrains, Zapier, and Wish. Why this role, why now E2B is the sandbox runtime behind Manus, Genspark, Lindy, Groq, Hugging Face, and a long list of AI labs and enterprise agent teams. We're a Series A company with over $37M raised, 8-figure revenue, and more than a billion sandboxes started. Almost all of it came from word of mouth. We have no content, no positioning beyond what the founders say on sales calls, and no launch process. Developers find us because someone they trust told them to. That works until it doesn't, and we'd rather build the machine while growth is strong than after it stalls. You'll be the first product marketer, and you'll decide how E2B explains itself to the world. You'll join before our next funding round, with equity priced accordingly. What you'll own - Positioning and messaging. What E2B is, who it's for, why it wins, and how that changes as the agent market changes. This is the foundation everything else in marketing sits on, and it doesn't exist yet. - Launches. Every product release goes through you: the narrative, the assets, the sequencing, the distribution. You set the launch cadence and hold engineering to it. - The content engine. Technical articles, comparison and migration pages, customer stories, launch content, the website. You write the first flagship pieces yourself, and you run the technical writer and video producer who scale it from there. - Pricing, packaging, and competitive. Usage-based pricing for infrastructure is a product marketing problem. You own the packaging story and the competitive positioning that sales and self-serve both rely on. - Sales enablement for the enterprise motion. Decks, one-pagers, objection handling, proof points. Built once, used everywhere. - A budget. Paid programs, sponsorships, tooling, freelancers. You propose it, you own it. - The function. You're the first person in it and we expect you to grow it as E2B grows. What's already in place Two growth engineers and a data scientist who own instrumentation, attribution, and the self-serve funnel, so what you ship will be measurable. A customer base that includes the companies most developers in this space want to learn from, and case-study material we've never written up. A community and ecosystem lead being hired alongside you. What we've learned so far Our buyers are engineers who trust benchmarks and code over adjectives. Comparison pages and docs-adjacent content convert better than anything else we've tried. Increasingly, developers find tools through LLM answers rather than search, and we think content should be built with that in mind. Treat these as inputs, not a plan; the plan is yours. First 90 days Write the positioning doc, with input from founders, sales, and the ten customers who know us best. Ship two customer stories and two flagship technical pieces. Run one launch end to end. Give us a content and launch calendar for the following two quarters with a clear argument for why it's the right one. How we'll judge year one Whether E2B can be explained in a sentence by someone who isn't us. Launch cadence and reach. Growth in content-attributed signups and enterprise pipeline that cites something we published. Whether the writer and video producer are shipping work you're proud of. Who you are - 5+ years in product or developer marketing for a technical product, with at least one stretch where you were the only marketer and it worked. - You write. Not "manage writers." Your portfolio has technical pieces you drafted yourself for a developer audience, and you can read code well enough to write about sandboxing, isolation, and runtime security without a ghostwriter. - You've done positioning from scratch and launched products that engineers adopted. - You understand usage-based pricing for infrastructure, or you've done pricing work somewhere close enough to learn fast. - You've been the number two on a product marketing team and want to be the one deciding. - You're comfortable being measured. Traffic isn't the deliverable; signups and pipeline are. Nice to have Experience with agent frameworks, model infrastructure, or sandboxes. Familiarity with answer-engine or SEO programs. A track record tying content to pipeline at a high-growth startup. WHAT IT’S LIKE TO WORK AT E2B We’re a fast-growing startup with in-person (4 days on-site, 1 day WFH) offices in San Francisco and Prague, Czech Republic. We already generate 8-figure revenue and work directly with top-tier AI companies like Manus, Genspark, Lindy, Groq, Artificial Analysis and other exciting teams pushing the frontier of AI. We offer healthcare, vision, and dental insurance, unlimited PTO, 401k, and a variety of perks for in-office employees.
Product Manager, Data Engine
Dyna Robotics builds general-purpose robots powered by a proprietary embodied AI foundation model with top-in-industry generalization and real-world performance. Already deployed with customers across multiple industries, our robots do commercial-grade work in the physical world. Our team comes from Google DeepMind, Meta, and Cruise, and we're backed by CRV, First Round, and other leading investors. The role We're hiring a Product Manager, Data Engine to own our deployment platform. The core of it is the data engine: everything that turns what happens in the field into training signal our models can learn from. It is the highest-leverage system we have for how fast our robots improve. The same role owns the tooling built around it, both the tools our field teams and customers use to run robots at their sites and the internal platform our research, engineering, and operations teams work in every day. At Dyna, internal tools are core products, and you'll own their roadmap and quality bar. Together, this is what turns working robots into a working fleet. WHAT YOU'LL DO The Data Engine - Decide what we capture. Define what every robot logs and what an episode has to contain for someone to diagnose a failure, then get it instrumented across the fleet. - Own the labeling schema. This is how we describe what robots do and what goes wrong, and it is where the job starts. A schema that matched the field six months ago won't match it today, and a pipeline running at high coverage against a stale schema is worse than useless because it looks healthy. You own the definitions, the audits, and the call on when it has to change. - Own the quality bar. Define how label quality is measured and audited, whether the work happens in-house or with vendors, and hold the line when coverage and quality pull against each other. That includes knowing where model-assisted labeling helps and where it quietly degrades quality while the coverage numbers look fine. - Own the rest of the loop. Episode and telemetry capture, annotation pipelines, model-behavior observability, and remote teleoperation for capturing recovery and intervention data. This is the loop that makes each deployment better than the last. Internal platform - Own the tools our own teams live in. Labeling and visualization systems, model evaluation tooling, and task management, used daily by researchers, engineers, and operations. - Design for technical, opinionated users. They want speed and direct access rather than guardrails, and they'll route around anything that slows them down. Own the UX and not just the capability: find the pain points these teams have stopped complaining about, and make them measurably faster. Operator experience - Own the tools that run robots on the floor. Setup, monitoring, evals, intervention, and escalation, used mid-shift by people with no technical background and no time to spare. That constraint shapes every decision in this area. - Own the customer-facing view. Decide what customers need to see to trust robots running in their business, which internal surfaces are on a path to them, and what has to change before they get there. - Spend real time on site. Watch robots fail and operators work. What a hotel GM needs in order to trust a robot on their floor is different from what our field team needs in order to fix one, and the requirements that matter most here are the ones nobody files a ticket about. WHAT YOU'LL BRING - 4+ years of product management experience owning labeling, annotation, or training data pipelines for ML systems end to end, from what gets captured through to what a model trains on. - Familiarity with ML infrastructure and how training pipelines consume the data you produce. - Experience designing and building tooling from scratch, both for technical users and for non-technical people doing time-sensitive work in real sites. - Comfort with systems that fail in physical ways. Robots break, sites are messy, and problems are rarely reproducible from a laptop. - Willingness to travel to customer sites regularly, and to be genuinely useful when you're there. BONUS POINTS FOR - Experience labeling video, multimodal, or time-series data rather than only images or text. - Background in robotics, autonomous vehicles, drones, or other fleet operations, particularly labeling perception or behavior data. - Experience with human-in-the-loop systems, teleoperation, or remote assistance products. - Experience with deployed hardware in customer environments and the operational reality that comes with it. - Experience with multi-site robot deployments. At Dyna Robotics, we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect. Don’t let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you’re passionate about robotics, no matter your discipline, we want to hear from you, even if you don't check every box.
Solutions Engineer
ABOUT DUST Work is being rewritten, and the people holding the pen are the ones who actually run it. With enterprise-grade governance, flexible model choice, and a collaborative interface for humans and agents to work together, Dust empowers AI Operators at the world’s fastest-moving companies to rewire how work gets done. With 70%+ weekly active users, people stick with Dust as much as they do with Slack and Notion. We don't get piloted and shelved. We land once, and spread. We're at an exciting stage of our journey, and growing fast. We're serving great customers https://dust.tt/customers like Datadog, 1Password, Cursor, Clay, Vanta and Persona, and aim to x5 our growth by the end of 2026. Dust is backed by Sequoia https://techcrunch.com/2024/06/27/dust-grabs-another-16-million-for-its-enterprise-ai-assistants-connected-to-internal-data/ with a determined team of optimists (coming from Stripe, OpenAI, and Stanford) who like to focus on users, ship fast, and don't take themselves too seriously while doing so. The Generalist named us among the Future 50 https://www.linkedin.com/posts/dust-tt_were-honored-to-be-recognized-on-the-generalists-activity-7359284343929741313-Rq04. TL;DR As a Solutions Engineer at Dust, you will act as the technical bridge between our sales team and prospective customers, demonstrating how our AI operating system transforms and adds value to their workflows. Your primary focus will be partnering with customers to showcase our solution through technical demonstrations, use case scoping and supporting technical evaluations. You will work closely with our Sales, Customer Success, and Product & Engineering teams to ensure successful customer engagements. OUR CULTURE - Product-First: Unlike others focused on building foundation models, we're laser-focused on creating delightful product experiences with existing LLMs. - Small, High-Impact Team: Join a team of alumni from Stripe, Square, OpenAI, and other top tech companies. We're intentionally keeping our team small and mighty – every individual has massive scope and impact. - Transparency & Collaboration: Our repository is open source, and we leverage serendipity between team members. We believe the best ideas emerge when the team shares information and insights openly. - Proactive Problem-Solving: If you see something broken, fix it—without waiting for permission. We don't wait for solutions - we create them. - Ship to Learn: We move fast and learn from real user feedback. - Intellectual Humility: We value strong convictions balanced with open-mindedness. Team members confidently advocate for their ideas while remaining receptive to new perspectives and evidence that might change their minds. If new data emerges, we adapt quickly. WHAT YOU’LL DO - Partner with the Sales team to articulate Dust’s value proposition to our prospects and customers and set them up for success - Provide compelling product demonstrations that showcase Dust's capabilities to both technical and business stakeholders - Help customers identify high-value use cases that align with Dust's capabilities and their specific business needs - Create and configure custom LLM agents in Dust to demonstrate practical applications - Own the technical evaluation end-to-end from customized demos to pilots, helping prospects by onboarding them onto the platform and driving pilot use-cases to completion - Represent the voice of the customer with Product & Engineering teams to ensure insights and feedback are being implemented into product strategy - Develop and maintain deep expertise in Dust's API capabilities and prompt engineering best practices - Educate customers on how to maximize value from generative AI within their workflows REQUIREMENTS - Meaningful experience in a combination of technical and customer-facing roles - Proven track record of helping customers unlock value from sophisticated software products - Experience conducting effective technical demonstrations and translating complex concepts to diverse audiences - Excellent communication and presentation skills with the ability to engage technical and business stakeholders - Strong technical aptitude with understanding of API concepts and generative AI prompt engineering principles - Passionate about educating customers of various backgrounds on new technologies - Ability to speak to both the technical and business value of a solution - Experience collaborating with cross-functional teams in fast-paced environments Ideal, But Not Required: - Experience with AI/ML technologies, particularly generative AI and LLMs - Background in productivity tools, knowledge management, or workflow automation - Coding experience to understand API implementations and create custom demos BENEFITS & COMPENSATION - Competitive compensation based on experience - We offer substantial support for relocation, including a stipend up to €10k, finding an apartment in Paris, and supporting you with all residence and work permit-related procedures - Significant equity package in a Sequoia-backed startup - Health insurance for you and your dependents - New MacBook Pro or Linux machine, monitor, keyboard, etc. - Regular team events and offsites LOCATION We're prioritizing building our team with an in-person culture at our offices in Paris, London, San Francisco, and New York because we value the magic that happens when talented people work closely together. We have an office-first culture. Some of the best things about building at Dust are the energy, the fast decisions, and the unexpected conversations that unlock a hard problem, which happen because we are in the same room. Being together is not a formality, it is how we do our best work, and it is something we actively protect. That said, we hire people with strong judgement and we extend that trust to how they manage their time. When working from home makes more sense for what you need to get done that day, we trust you to make that call. WHY DUST The models are powerful enough. What's missing is the product layer where AI meets how companies actually work. That's what we're building: the infrastructure that lets any team turn scattered knowledge and tools into coordinated execution with agents they build, own, and run themselves. We use Dust ourselves every day. We get to shape how humans and agents collaborate while solving our own problems with the product we ship. That loop is rare, and it's why we move fast. If you're excited about defining a new category and want to join a determined team of optimists who focus on users, ship fast, and don't take themselves too seriously, we'd love to talk. Even if you don't check every box in our requirements, we encourage you to apply. We value diverse perspectives and backgrounds, and we're more interested in your potential and passion than a perfect match to our checklist. Learn how we think and work. - Our product constitution, https://blog.dust.tt/a-first-version-of-our-product-constitution/ a story about our mission - Your Next Co-Worker Isn’t Human https://www.youtube.com/watch?v=xIvlRWEXqqw, Stanislas Polu, VivaTech 2026. A conversation about AI agents taking on larger parts of work and how teams collaborate with them. - Dust: Gabriel Hubert on Enterprise AI https://www.nasdaq.com/videos/dust, Gabriel Hubert, Nasdaq, published May 7, 2026. On Dust’s approach to enterprise AI and building the company in Europe.
Enterprise AI Architect
ABOUT DISTYL AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. WHAT WE ARE LOOKING FOR We are looking for a senior Enterprise AI Architect to serve as the long-term technical partner to some of Distyl’s most strategic Fortune 500 customers. You will operate more like a senior technical partner than a traditional pre-sales architect: build trust with C-suite and technical leaders, bring a strong point of view on where AI can create meaningful business value, shape the solution with the customer, and stay accountable for the technical relationship beyond signature. This role sits in Engineering and works closely with Go-to-Market, Product, and Forward-Deployed Engineering. You will lead the technical arc of an account from early technology conversations and problem shaping through architecture, feasibility, and SOW; for qualified late-stage pursuits, you will partner with forward deployed engineers to drive implementation of solutions. After close, the Technical Delivery Lead owns day-to-day execution while you remain attached for architecture reviews, steering moments, difficult decisions, and expansion. This is a senior individual-contributor role for someone who has built and delivered production systems, can hold a room with executives, and can translate between business ambition and engineering reality. Success means customers view you as a trusted technical advisor, GTM gets technically credible proposals, and delivery inherits scopes that survive contact with production. KEY RESPONSIBILITIES - Own the strategic technical relationship. Serve as the primary technical counterpart for strategic accounts, building trust with CIO/CTO-level leaders, enterprise architects, and business executives. Help customers identify where AI can materially change an operation, pattern-match from prior deployments, and shape an ambitious but deliverable technical vision. - Own architecture, feasibility, prototypes, and technical SOW quality. Lead joint solution architecture with customer teams, applying Distyl’s platform and technical primitives to real enterprise systems. Use prototypes and demos to validate key assumptions where needed, and own the technical content of the SOW, including integrations, data access, deployment model, dependencies, assumptions, and risks. - Qualify opportunities and shape technically credible solutions. Assess whether opportunities are well-suited for AI, evaluate data, systems, security, integration, and organizational constraints, and make the call on technical feasibility before Distyl commits to scope. - Turn customer patterns into reusable assets and product feedback. Translate recurring needs, architecture patterns, security constraints, and deployment learnings into reusable technical assets and concrete feedback that influences Distyl’s platform, product, and engineering roadmap. - Carry the technical thread from first conversation through successful delivery. Stay engaged through architecture reviews, executive steering, major tradeoffs, risk escalations, and expansion opportunities, while empowering the delivery lead to own execution. WHO YOU ARE Required - 8+ years of relevant experience across engineering, enterprise architecture, forward-deployed engineering, solutions architecture, or similar roles, with substantial customer-facing responsibility. - Hands-on production delivery experience. You have designed, built, and shipped Enterprise-grade Agentic AI/ML systems and can reason credibly about implementation tradeoffs, reliability, integration, scale, security, and operating constraints. - Demonstrated ability to operate as a senior technical advisor to executives: you can build trust, develop a point of view, shape ambiguous problems, influence decisions, and handle high-stakes technical conversations without relying on a script. - Proven ownership of complex enterprise solution architecture and scope, including the ability to write technical SOW content and align customer teams, GTM, and delivery around what is actually buildable. - Ability to work effectively with FDE / Delivery / Product & Strategy teams — bringing them in at the right time, using their current implementation depth, and maintaining continuity. - Strong working knowledge of APIs, integrations, cloud and enterprise architecture, data flows, security considerations, and modern AI systems; coding fluency to prototype, inspect systems, and engage deeply with engineers. - Deep domain expertise in one or more enterprise areas such as customer support, voice, MarTech, Cybersecurity, IAM, or Document processing. - Able to travel 25% and meet onsite with customer teams; able to work from our New York or San Francisco office Tuesday–Thursday. Preferred - Background in an FDE, engineering, or technical consulting organization where you owned both customer outcomes and technical decisions. - Experience in a partner-like role at a consulting firm, high-growth technology company, or enterprise software company with long, C-suite-led sales cycles. - Experience at an early-stage startup and comfort operating in ambiguous environments where the playbook is still being built. WHAT WE OFFER - The base salary range for this role is $200,000 - $275,000 depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package - 100% coverage of medical, dental, and vision insurance for employee and dependents - Flexible time off - Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources - Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot - Complimentary in-office lunches and snacks provided - Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems - Ownership of high-impact projects across top enterprises - A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in-office. #LI-Hybrid We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.
Technical GTM Enablement Manager
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. OPPORTUNITY Deepgram is expanding our enablement function, and we're hiring our first Technical GTM Enablement Manager. This role is the force multiplier for the technical side of our revenue organization. You will own how our pre-sales and post-sales technical teams ramp, stay current, and prove they are ready, sitting at the intersection of Product, Applied Engineering, Customer Success, and Sales. Our technical field teams run demos, guide architecture decisions, troubleshoot live integrations, and take customers to production. You are not here to teach them their jobs. You are here to make what our best technologists already do repeatable for everyone else, and to get new hires there faster. This is not a training delivery role, and it is not externally facing content creation. Most of what should exist does not exist yet. You will build it. WHAT YOU'LL DO - Own onboarding and ramp for technical GTM roles, designing and continuously improving a structured program that gets new hires to productivity faster and creating a consistent technical standard across teams. - Build technical field framework and playbooks, including: - Technical discovery with buyers, developers, and evaluators - POC and evaluation standards, including clear technical and business success criteria - Architecture guidance for our most common customer patterns - Technical handoffs across pre-sales and post-sales - Escalation readiness, turning what we learn from individual customer issues into reusable guidance - Build and run technical certifications, keeping it current as the platform changes rapidly underneath it. - Lead technical readiness for launches, partnering with Product and PMM so technical teams are ready before GA rather than after. - Turn subject matter expertise into scalable enablement, pulling what sits in the heads of Product, PMM, and our strongest field technologists and turning it into something repeatable. - Partner with Sales Enablement where the sale turns technical, including technical discovery, evaluation strategy, competitive differentiation, and solution positioning - Operate AI-first, building the tools, agents, and workflows that let a small enablement function serve a growing technical organization. YOU'LL LOVE THIS ROLE IF YOU - Came up in the field and would rather fix the system than keep carrying the workaround. - Are energized by earning credibility with senior technical people, and have the background to do it. - Believe in the power of AI to transform productivity, and are eager to harness cutting-edge tools to optimize performance. - Would rather ship something useful this month than design something perfect for next quarter. - Are passionate about Deepgram's mission to redefine what's possible with speech technology. - Value clarity, accountability, and moving quickly without a lot of process or hierarchy. IT'S IMPORTANT TO US THAT YOU HAVE - 5+ years in technical, customer-facing roles: solutions engineering, solutions architecture, customer success engineering, technical account management, implementation, or forward-deployed work. - Real time spent building enablement for technical teams, not just delivering it. - Hands-on fluency with APIs, SDKs, integrations, and developer workflows. You can run a live demo, read a customer's integration and see what is wrong, troubleshoot L1-style issues, and hold a genuine architecture conversation. Production code is not required. Hand-waving does not pass. - Experience building onboarding, certification, or technical development programs that people actually finished. - Demonstrated ability to get content out of subject matter experts who have no time for you, and ship anyway. - Something you have built, a tool, agent, script, or workflow, that permanently eliminated recurring work. In your application, tell us what it was, what it replaced, and what it is still doing today. - An AI-native operating model: specific workflows that structurally depend on AI, and a clear account of how you would rebuild them if those tools disappeared tomorrow. IT WOULD BE GREAT IF YOU HAD - Experience with speech recognition, TTS, voice agents, LLM orchestration, or other developer-first API products. - Experience enabling both pre-sales and post-sales technical roles, and a point of view on how they differ. - Working fluency with scripting or agent building: Python, TypeScript, workflow tools, agent frameworks, or equivalent. You don't need to be a software engineer, just dangerous enough to ship working systems. - Strong writing and narrative skills, especially for turning complex technical concepts into clear, usable field guidance. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Staff Product Manager, Agentic Experiences (Former...
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. The Opportunity The way developers find and adopt an API is changing. More and more, an AI coding agent discovers us, chooses the provider, writes the integration, and consumes our API, often with no human ever at the console. Deepgram is looking for a Staff Product Manager to own our product experience for that agent across its whole life with us: how an agent discovers and chooses Deepgram, how it integrates, how it uses the product in production, and how it verifies its own work. You will own that experience end to end, and you will build the system that keeps improving it as agent behavior changes. You report to the VP of Self-Serve. This is a product management role in the conventional sense: you own the product, its direction, and its decisions, and engineering builds it. Two things set the role apart, and both are required — you are a former engineer who still builds to think and to prove a point, and you are deeply AI-native, with shipped work to show for it. You will prototype, read and write code, and reason with engineering at depth; your job is to own the product, not to be its implementing engineer. What You'll Do - Own the agent's experience of Deepgram across its lifecycle — discovery and recommendation, integration and onboarding, production use, and verification. - Stand up a system that measures and optimizes every stage of the funnel for agents, and keep it current as agent behavior changes. - Own the product surfaces specific to the agent experience: signup and authentication, the trial-key and token defaults and programmatic key provisioning, console onboarding, and the verification tooling that lets an agent confirm its integration is actually correct. - Set the requirements for what the agent experience needs from the shared developer platforms — SDK ergonomics, the agent-readable documentation and llms.txt, the MCP server, the CLI, the skills package, and starter templates — and prototype the changes directly, in partnership with the team that owns those platforms. - Stand up the operating system your work runs on — the rhythms of business, data-driven optimization, and the experimentation platform — by building it in-house or by researching and deploying the best tools available. - Turn the scale of agent traffic into fast feedback loops, so the product improves as agents use it. - Bring the product's point of view on agents as users: what they need, where they fail, and what to change, grounded in how models actually retrieve, choose, and integrate. You'll Love This Role If You - Were an engineer, moved to product to own outcomes, and never stopped building. - Think like an architect and can design and stand up a self-optimizing system across discovery, onboarding, and integration. - Have felt, first-hand, how an AI agent succeeds or fails at a real integration, and have strong opinions about why. - Want to own a product that is becoming the front door of the business, at the moment it is becoming that. - Are energized by being early — defining the practice, not inheriting it. It's Important to Us That You Have - Excellent product management judgment. You own product and roadmap, set direction, decide under uncertainty, ship outcomes, and lead cross-functional work without authority. You can show the results. - A former engineer's depth (required). You were a senior software engineer, or more, before you moved to product. You architect and ship production systems, you read and write real code, and you reason with engineering at their level. You are not a vibe coder who assembles what a tool generates. - Deep AI fluency, proven by shipped work (required). You have personally built and shipped AI software that goes well beyond prompt files and markdown — agents, MCP servers, CLI tools, agent and evaluation harnesses, real model-integrated tools — and it is public. Send us the GitHub; we will read the code, the commits, and the design. - Proven ability to stand up a complete system from scratch — the rhythms of business, the reporting and optimization, the experimentation platform — yourself or in-house, or by researching and deploying the right tools. - PLG and developer-product fluency. You understand how developers, and increasingly their agents, adopt APIs, and you understand product-led growth. - The judgment to distrust a number or a passing test before you build on it. You ask whether it is real, as a reflex. - Clear communication with executives: you lead with the decision, keep your method in reserve, and hold up under pushback without either caving or digging in. It Would Be Great If You Had - Built specifically for AI agents as the consumer — MCP servers, agent harnesses, CLI tools, agent-readable docs, tool definitions, or evals for agent output. - Experience with voice, audio, or real-time streaming systems. - A track record of open-source work with real adoption. - Time in a company with both a self-serve and an enterprise motion. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Staff Product Designer, Conversational AI
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. Note: This is a remote role based in Pacific Time, with a preference for candidates located in San Francisco. ABOUT THE ROLE Deepgram builds the models and APIs that put voice agents into production at scale. What decides whether those agents feel human is not a screen. It is whether the agent knows when you have finished speaking, what it does when you cut it off, how it recovers from a misheard word, how it confirms something consequential before acting, and how it covers the milliseconds it cannot remove. Today those decisions live inside prompts and pipeline config, made ad hoc by whoever is closest to the problem. No one owns them end to end. We are hiring a Staff Conversational Designer to own them. You will define how Deepgram's voice agents converse: persona, turn-taking, repair, confirmation, and pacing. You will work directly with ML and Engineering on the tradeoffs that make those behaviors real, including endpointing, barge-in, and latency budgets. You will build the evals that tell us whether a conversation is actually good, and publish the guidance and reference experiences that show developers how to build natural conversations on the Voice Agent API. This is a leading edge role. Very few companies have a titled equivalent. You will be defining this discipline at Deepgram, not inheriting it. You'll report directly to the Director of Product Design. This is a Staff IC role, and your impact shows up mostly in the leverage you create for others: the patterns our own experiences run on, and the guidance our customers build against. Your first chapter: a documented persona and voice system, and turn-taking and repair behavior designed and shipped with Engineering. From there, scope expands into conversational-quality evals and developer-facing guidance. WHAT YOU’LL DO - Define the persona and voice system for Deepgram voice agents, and keep it coherent across experiences and use cases - Design turn-taking, barge-in, and end-of-turn behavior with ML and Engineering, tuning responsiveness against the risk of interrupting the user, per use case - Design conversational repair, no-match and no-input handling, and confirmation strategy, including guardrails that require confirmation before high-stakes actions - Own latency-aware pacing and perceived responsiveness: brevity, backchanneling, hold and filler speech, all against real-time budgets - Establish conversational-quality evals and a transcript review practice that turns production failures into a repeatable design loop - Build the reference agent experiences and developer-facing design guidance that demonstrate best-practice conversation on the Voice Agent API - Partner with ML and Research on ASR and TTS behavior, and on the quality criteria that define a good conversation - Set the conversation-design principles, review standards, and shared vocabulary the broader team adopts YOU’LL LOVE THIS ROLE IF YOU - Believe conversation is an interface with real craft behind it, not a prompt someone tunes on the side - Want the hard real-time problems: endpointing, barge-in, and the half-second you cannot design away - Get energized by being foundational, defining what good means for a discipline that does not exist here yet - Think the fastest way to raise quality is to make it measurable, then make it repeatable - Are excited by a category still inventing its interaction patterns, where the work is invention rather than iteration IT’S IMPORTANT TO US THAT YOU HAVE We care more about expertise and leadership than years of experience. - Deep experience designing conversational behavior for LLM-based voice agents or assistants, not only scripted IVR flows - Real fluency with the speech pipeline, from ASR through LLM to TTS, and a working understanding of where design decisions actually live inside it - A track record designing turn-taking, interruption, repair, and confirmation patterns that shipped and held up in production - Evidence of building quality measurement into the practice: evals, transcript review, benchmarks, or a structured failure-analysis loop - Exceptional writing craft, including sample dialogs, design guidance, and documentation that others can build against - Experience influencing engineering and ML partners on behavior they own, without authority over them - Experience designing for developers or technical users, including APIs, SDKs, and documentation surfaces - A working AI practice, with a point of view on where these tools help and where they mislead IT WOULD BE GREAT IF YOU HAD - Time on a named assistant or a production voice agent platform - Practice with Wizard of Oz testing and sample dialog methods - Hands-on work with eval tooling for LLM or voice quality - Experience in high-stakes or regulated conversation domains where confirmation and recovery carry real cost - Multilingual or cross-locale conversation design experience - Background in high-growth B2B companies with both self-serve and enterprise motions Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Head of AI Enablement Engineering
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. THE OPPORTUNITY Deepgram's ambition is to build a generational company with a small, exceptional team — which only works if every engineer and every function operates with serious AI leverage. We're looking for a Head of AI Enablement Engineering to own that mission end to end: making Deepgram one of the most AI-native companies in the world, in practice and not just in principle. This is a build-first leadership role, not a steward or training role. You'll personally evaluate tools, build the agents and workflows that show what great looks like, and set the standards that the rest of the company adopts. You'll turn our AI-native strategy into shipped capability — reusable agents and skills, MCP integrations, paved-road workflows, and the enablement hub and patterns that let any team go from idea to working tool fast and safely. You'll partner closely with Engineering, Platform/Internal Tools, People Ops, and functional leaders across the company, and you'll be measured on real outcomes: adoption, productivity, and the quality of what people build. You'll lead largely through building and influence, with the runway to grow a small team and a network of champions as the function scales. It's a high-visibility seat with executive sponsorship and a mandate to set direction where there is no established playbook. WHAT YOU'LL DO - Own and drive AI enablement engineering across Deepgram — the strategy, the standards, and the hands-on building that make AI leverage real in every function. - Personally evaluate, prototype with, and make the calls on the AI tools, agents, models, and orchestration layers Deepgram adopts; avoid tool sprawl and make pragmatic build-vs-buy decisions. - Build the reference implementations: reusable agents and skills, MCP servers, paved-road workflows, prompt and pattern libraries, and the enablement hub where the best internally-built tools are surfaced and elevated. - Set and run the company-wide AI adoption strategy — the metrics, milestones, and reporting cadence leadership uses to track progress, framed around measurable productivity and quality, not activity. - Partner with Platform/Internal Tools, Security, and Data to define guardrails that are embedded into platforms rather than enforced through gates — safe-use patterns, access, and data handling that make adoption easier, not harder. - Build and lead a distributed champions network embedded in teams, and grow a small central team over time as impact scales. - Partner with People Ops on AI-native onboarding and fluency, so new and existing teammates do real reps inside the tools and leave the system better than they found it. - Stay ahead of a fast-moving landscape and translate emerging AI capabilities into pragmatic, Deepgram-ready practice. YOU'LL LOVE THIS ROLE IF YOU - Want to define how an entire company works with AI — and you'd rather build the proof than write the memo. - Are energized by ambiguity and a blank page, and you set direction where there's no playbook yet. - Are hands-on and current: you build agents and workflows yourself and can sit across from senior engineers as a peer on day one. - Care about real outcomes — adoption, time saved, quality — not vanity metrics or shelf-ware. - Like operating across an org, bringing skeptical teams along through demonstrated value rather than mandate. - Believe a small, AI-leveraged team can outbuild a much larger one. IT'S IMPORTANT TO US THAT YOU HAVE - A strong engineering background with the hands-on ability to build production-quality agents, tools, and automations yourself. - Deep, current fluency with the modern AI tooling landscape — coding agents, LLM application patterns, prompting, retrieval, MCP/agent tooling, and orchestration. - A track record of driving technology adoption and changing how people work at scale, in environments that didn't start out asking for it. - The ability to operate across business and technical functions and influence without direct authority, including credibility with senior engineering leaders. - Strong product and platform instincts — you treat enablement as a product, with users, adoption, and a roadmap. - Excellent communication — you can demo, document, evangelize, and report outcomes to executives in plain language. - Comfort defining safe-use guardrails and data-handling practices in partnership with Security and Platform. IT WOULD BE GREAT IF YOU HAD - Experience standing up an AI enablement, developer productivity, or engineering effectiveness function from scratch. - Background building internal platforms or developer-facing tooling that engineers actually adopted. - Experience leading a small team and/or a distributed champions/center-of-excellence model. - Familiarity with enterprise AI search and knowledge tooling (e.g., Glean, Notion AI) and agent orchestration frameworks. - A point of view on measuring developer productivity and AI impact, with the nuance that entails. - Experience in a fast-moving, AI-native engineering organization. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Embedded AI Engineer, On-Device Models
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. ABOUT THE ROLE Deepgram's speech models are among the fastest and most accurate in the world, and we have deep machinery for running them on NVIDIA GPUs. Our customers need them on everything else: non-NVIDIA accelerators, embedded SoCs, mobile application processors, DSPs and NPUs, and purpose-built devices with tight memory, compute, thermal, and power budgets. When a target platform's standard kernels and runtime can't run a Deepgram model well enough, someone has to go below them. That is this role. As an Embedded AI Engineer on the Partner Platform Engineering team, you work at the lowest layer of our edge stack. You write and optimize custom kernels and operators for specific hardware, collapse models onto device-specific execution units, and do the target-side quantization and assembly-level tuning that standard toolchains can't. You hand what you build up to Applied ML Engineers, who fit Deepgram models to your kernels. Your work is what makes a new hardware platform viable for Deepgram at all. This role is a great fit for a senior embedded engineer who has spent their career close to the metal and wants to point that at speech AI, or a staff-level engineer who wants to define how Deepgram's models get onto new silicon. We'll set the level to your experience. WHAT YOU'LL DO - Write and optimize custom kernels and operators (C, C++, Rust, and platform assembly or intrinsics) for non-NVIDIA accelerators, embedded SoCs, DSPs, and NPUs where the vendor's standard operator set is insufficient for Deepgram models. - Own target-side optimization: collapse models onto device execution units through quantization, operator fusion, memory layout, and architecture-specific compilation to meet latency, memory, power, and thermal budgets. - Integrate with vendor NPU/DSP toolchains and edge inference runtimes, and extend them with custom operators when the graph doesn't map cleanly. - Deliver kernels and runtime components as reusable building blocks that Applied ML Engineers can target when adapting models, with clear interfaces and documented constraints. - Build performance-critical runtime code for embedded environments, including embedded Linux, bare-metal, and RTOS targets. - Establish per-platform benchmarking and validation for latency, accuracy, power, memory footprint, and utilization, and catch regressions before they ship. - Partner with silicon and platform vendors on SDK integration and low-level performance tuning for new chipsets and reference platforms. - Feed hardware constraints back to Applied ML and Research so model designs are easier to land on constrained targets. YOU'LL LOVE THIS ROLE IF YOU - Find deep satisfaction in making a large model run on hardware that was never meant to run it, and still hitting accuracy and latency targets. - Reach for the profiler and the ISA manual before you reach for a bigger chip. - Would rather write the kernel than wait for the vendor to ship it. - Care about the details that don't show up in a cloud benchmark: cold start, power draw, thermals, memory fragmentation, cache behavior. - Prefer hard, constrained, ship-it problems over open-ended research. - Care about the details that don't show up in a cloud benchmark: cold-start time, power draw, thermals, and memory fragmentation. IT'S IMPORTANT TO US THAT YOU HAVE - Experience delivering production systems on resource-constrained hardware — embedded systems, mobile, edge AI, or small low-power devices. - Strong proficiency in C, C++, and/or Rust, with experience writing performance-critical code for constrained environments. - Hands-on experience with model optimization for on-device deployment, including quantization, pruning, knowledge distillation, or architecture-specific compilation. - Familiarity with edge inference runtimes (e.g., ONNX Runtime, TensorRT, TFLite, ExecuTorch) and/or vendor-specific NPU/DSP toolchains. - A strong understanding of hardware-software interaction — CPU/GPU/NPU/DSP architectures, memory hierarchies, fixed-point/integer arithmetic, and power management — and how they affect inference performance. - Experience working close to the metal: bare-metal or RTOS environments (e.g., FreeRTOS, Zephyr), embedded Linux, or microcontroller and edge SoC development. - Strong communication skills and a builder mindset — you can scope an ambiguous optimization problem, drive it to a measurable result, and explain the tradeoffs clearly. IT WOULD BE GREAT IF YOU HAD - Experience with real-time audio processing on embedded platforms — DSP pipelines, audio codec optimization, wake-word or always-on listening, or streaming inference on microcontrollers and edge SoCs. - Depth in ML optimization techniques — custom quantization schemes, mixed-precision inference, or neural architecture search for edge targets. - Background in hardware evaluation and benchmarking — systematically comparing accelerators, SoCs, or GPUs for specific workload profiles. - Experience shipping AI features in consumer products at scale, and the instinct for what "production quality" means on a battery-powered device. - Familiarity with model compilation and optimization toolchains and their tradeoffs across hardware targets. - Experience with secure, robust on-device deployment practices — code signing, encrypted model storage, and safe update mechanisms. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Director, Text-to-Speech Synthesis Research
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. THE OPPORTUNITY We're looking for a Director of Research to own our Text-to-Speech program end to end — the research strategy, the technical bets, and the models that ship. This is a hands-on leadership role: you set direction and stay in the details, shaping architectures, experiments, training strategy, and evaluation. You'll also build the team and operating model that let exceptional researchers move fast without lowering the bar. The mandate is broad: advance the state of the art in speech generation, and turn those advances into models in production. WHAT YOU'LL DO - Own the TTS research and model roadmap — decide which technical directions can materially move speech-generation quality, including the expensive and non-obvious ones, and recognize when an approach should change or die. - Drive advances across neural audio modeling, prosody and expressiveness, controllability, multilingual speech, voice identity and consistency, data and training strategy, post-training, and inference performance — and make sure they land as measurable production gains. - Stay deeply technical: review research, challenge assumptions, design experiments, diagnose model failures, and take on the highest-leverage problems yourself. - Build evaluation and benchmarking that explains why models improve, not just whether they did — automated metrics alongside human perceptual assessment. - Lead a mix of individual contributors and tech lead managers. Hire and develop both, hold an exceptionally high technical bar, grow senior researchers into technical leaders, and set direction across sub-teams while pushing decisions down to the people closest to the work. - Partner with engineering and product leadership on ship-readiness, and represent Deepgram's TTS research internally and externally. YOU'LL LOVE THIS ROLE IF YOU - Want to own a frontier-model program end to end rather than optimize one slice of someone else's agenda. - Care about the breakthrough and the ship in equal measure. - Still love training runs, failed evals, and architecture arguments, even as most of your impact now comes through the people you lead. - Get energy from deciding which bets are worth making when the answer isn't obvious and the experiments are expensive. YOU MUST HAVE - Deep expertise in modern TTS, speech generation, or audio generative modeling, with a track record of personally training and improving large-scale neural models. - Command of the modern speech-generation stack and the open problems behind naturalness, expressiveness, controllability, robustness, voice consistency, and inference cost. - A history of setting research direction under genuine uncertainty: prioritizing experiments, allocating compute and researcher time, and killing approaches that aren't working. - Experience leading researchers and research engineers through other technical leaders — developing tech lead managers or equivalent, setting direction across sub-teams — while staying technically influential yourself. - AI as your default mode of work, not an occasional tool. You've rebuilt how you and your team operate around it, and you have a specific, earned view of what it still can't do in speech research. - The ability to make complex technical tradeoffs legible to product, engineering, and executive audiences. IT'D BE GREAT IF YOU HAD - TTS or generative-audio models deployed at meaningful production scale. - Built or substantially scaled a high-performing AI research organization. - Sophisticated evaluation systems for generative speech; expressive or multilingual generation, voice cloning and adaptation, or controllable generation. - Recognized external contributions — publications, open source, patents, invited talks — in speech synthesis, neural audio codecs, speech language models, or multimodal models. - Experience in fast-moving startup or research environments that routinely take models from idea to production. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Director of Research, Text to Speech
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. THE OPPORTUNITY We're looking for a Director of Research to own our Text-to-Speech program end to end — the research strategy, the technical bets, and the models that ship. This is a hands-on leadership role: you set direction and stay in the details, shaping architectures, experiments, training strategy, and evaluation. You'll also build the team and operating model that let exceptional researchers move fast without lowering the bar. The mandate is broad: advance the state of the art in speech generation, and turn those advances into models in production. WHAT YOU'LL DO - Own the TTS research and model roadmap — decide which technical directions can materially move speech-generation quality, including the expensive and non-obvious ones, and recognize when an approach should change or die. - Drive advances across neural audio modeling, prosody and expressiveness, controllability, multilingual speech, voice identity and consistency, data and training strategy, post-training, and inference performance — and make sure they land as measurable production gains. - Stay deeply technical: review research, challenge assumptions, design experiments, diagnose model failures, and take on the highest-leverage problems yourself. - Build evaluation and benchmarking that explains why models improve, not just whether they did — automated metrics alongside human perceptual assessment. - Lead a mix of individual contributors and tech lead managers. Hire and develop both, hold an exceptionally high technical bar, grow senior researchers into technical leaders, and set direction across sub-teams while pushing decisions down to the people closest to the work. - Partner with engineering and product leadership on ship-readiness, and represent Deepgram's TTS research internally and externally. YOU'LL LOVE THIS ROLE IF YOU - Want to own a frontier-model program end to end rather than optimize one slice of someone else's agenda. - Care about the breakthrough and the ship in equal measure. - Still love training runs, failed evals, and architecture arguments, even as most of your impact now comes through the people you lead. - Get energy from deciding which bets are worth making when the answer isn't obvious and the experiments are expensive. YOU MUST HAVE - Deep expertise in modern TTS, speech generation, or audio generative modeling, with a track record of personally training and improving large-scale neural models. - Command of the modern speech-generation stack and the open problems behind naturalness, expressiveness, controllability, robustness, voice consistency, and inference cost. - A history of setting research direction under genuine uncertainty: prioritizing experiments, allocating compute and researcher time, and killing approaches that aren't working. - Experience leading researchers and research engineers through other technical leaders — developing tech lead managers or equivalent, setting direction across sub-teams — while staying technically influential yourself. - AI as your default mode of work, not an occasional tool. You've rebuilt how you and your team operate around it, and you have a specific, earned view of what it still can't do in speech research. - The ability to make complex technical tradeoffs legible to product, engineering, and executive audiences. IT'D BE GREAT IF YOU HAD - TTS or generative-audio models deployed at meaningful production scale. - Built or substantially scaled a high-performing AI research organization. - Sophisticated evaluation systems for generative speech; expressive or multilingual generation, voice cloning and adaptation, or controllable generation. - Recognized external contributions — publications, open source, patents, invited talks — in speech synthesis, neural audio codecs, speech language models, or multimodal models. - Experience in fast-moving startup or research environments that routinely take models from idea to production. Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Backend Software Engineer - Engine Team (Voice Age...
COMPANY OVERVIEW Deepgram is the leading platform underpinning the emerging trillion-dollar Voice AI economy, providing real-time APIs for speech-to-text (STT), text-to-speech (TTS), and building production-grade voice agents at scale. More than 200,000 developers and 1,300+ organizations build voice offerings that are ‘Powered by Deepgram’, including Twilio, Cloudflare, Sierra, Decagon, Vapi, Daily, Cresta, Granola, and Jack in the Box. Deepgram’s voice-native foundation models are accessed through cloud APIs or as self-hosted and on-premises software, with unmatched accuracy, low latency, and cost efficiency. Backed by a recent Series C led by leading global investors and strategic partners, Deepgram has processed over 50,000 years of audio and transcribed more than 1 trillion words. There is no organization in the world that understands voice better than Deepgram. COMPANY OPERATING RHYTHM At Deepgram, we expect an AI-first mindset—AI use and comfort aren’t optional, they’re core to how we operate, innovate, and measure performance. Every team member who works at Deepgram is expected to actively use and experiment with advanced AI tools, and even build your own into your everyday work. We measure how effectively AI is applied to deliver results, and consistent, creative use of the latest AI capabilities is key to success here. Candidates should be comfortable adopting new models and modes quickly, integrating AI into their workflows, and continuously pushing the boundaries of what these technologies can do. Additionally, we move at the pace of AI. Change is rapid, and you can expect your day-to-day work to evolve just as quickly. This may not be the right role if you’re not excited to experiment, adapt, think on your feet, and learn constantly, or if you’re seeking something highly prescriptive with a traditional 9-to-5. Opportunity Deepgram is looking for a backend software engineer to lead the design and implementation of Deepgram’s Voice Agent product. You will design and implement secure, robust, and scalable services for speech processing; build integrations supporting telephony providers, RAG systems, and diverse deployment scenarios; engineer for testability and observability within a complex chain of AI models; and more. Your skill at building highly reusable code that overcomes technical challenges is paired with an intuition for delightful user experiences. You will be a critical voice in Deepgram’s Product and Engineering teams, driving high impact products from start to finish. What You’ll Do - Improve Deepgram’s core inference services including areas in networking, speech processing, model orchestration, and observability - Develop integrations with cutting edge in-house, third-party, and open-source AI models for perception and managing conversational dynamics - Debug complex system issues that include networking, scheduling, and highly concurrent workloads - Rapidly customize backend services to support our customer needs - Partner with Product to design and implement new services, features, and/or products end to end You’ll Love This Role If You - Thrive in a fast-paced, impact-driven environment where learning new skills on-the-fly is not only encouraged but a regular necessity - Enjoy balancing decisions about product and feature maturity to decide when to make minimally invasive changes versus when to incorporate detailed design work It’s Important To Us That You Have - 3+ years of experience in an industry role - Programming experience in Rust (or C, C++), with competence in Python - Excellent communication and organizational skills, both written and verbal. - A high level of experience and understanding of version control; preferably git. - Comprehensive experience with UNIX-style systems. It Would Be Great If You Had - Experience with low-latency, multi-model orchestration for AI-enabled applications - Experience with audio processing Notice: We're aware of individuals impersonating Deepgram recruiters. All legitimate Deepgram recruiting communication comes from an @deepgram.com http://deepgram.com email address. If you've received a message claiming to be Deepgram, please forward it to careers@deepgram.com.
Staff Software Engineer, Agent Platform
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Agent Platform team builds the runtime and model orchestration layer that powers Decagon’s agents in production. This is the orchestration layer that turns workflows, tools and guardrails into a reliable, low-latency, and delightful experience for end users. At the core of this work is the agent harness: the routing, execution logic, tool orchestration, and control-plane systems that determine how an agent behaves in a live conversation. The team owns the full execution lifecycle of each conversation—from selecting workflows and orchestrating multiple models (e.g., router/planner/supervisor patterns), to coordinating tool calls, enforcing safety constraints, and communicating back to the user. The team operates across both real-time systems (e.g., voice interactions with strict latency requirements) and longer-horizon execution (supporting more complex reasoning and workflows). Our research shows that an agent’s task execution reliability increasingly depends on the orchestration layer that wraps around it. This is highly experimental, frontier-style engineering. The team continuously analyzes real-world failures, builds feedback loops through offline evaluation and online experimentation, and iterates quickly to improve quality, reliability, and capability. As model capabilities evolve, the team regularly rethinks system design to push agent performance forward in production. About the Role As a Staff Software Engineer on the Agent Platform team, you will design and build the systems that govern how Decagon agents operate in real-world environments. You will own complex, distributed systems that sit at the heart of the agent runtime: execution frameworks, model orchestration logic, and experimentation platforms that ensure agents are fast, reliable, and continuously improving. Your work will directly impact how agents reason, take actions, and deliver outcomes across millions of interactions. This role operates in a fast-moving, ambiguous space with tight feedback loops. You’ll move fluidly between diagnosing production issues, designing new system abstractions, and running experiments to improve agent behavior. You’ll collaborate closely with Research, Infra, and Product teams to ship improvements safely and at scale. In this role, you will - Design and evolve agent harnesses that power different product experiences - Build core runtime systems, including AOP execution and multi-model orchestration - Develop control-plane logic for routing, planning, and tool invocation with strong safety guarantees - Optimize agent systems for latency, reliability, and production correctness - Analyze real-world failures and use data to drive iterative improvements - Build and operate online experimentation (A/B testing) and contribute to offline evaluation frameworks - Improve observability, testing, and simulation systems to ensure safe, measurable progress - Contribute to voice and real-time systems (e.g., transcription pipelines, turn-taking, latency improvements) - Continuously adapt orchestration systems as model capabilities evolve Your background looks something like this - Strong experience building distributed systems or backend platforms in production environments - Comfort working in ambiguous, fast-moving environments with rapid iteration cycles - Experience owning systems end-to-end, from design through production and iteration - Familiarity with experimentation, evaluation, or data-driven product improvement loops - A track record of improving system reliability, performance, and observability - Ability to debug complex systems and identify root causes of failures Even better - You’ve built or worked on agent harnesses, orchestration layers, or execution frameworks - You think in terms of control planes, feedback loops, and system-level optimization, not just features - You’re excited about diagnosing failure modes and iterating toward measurable improvements - You care deeply about production quality—not just making systems work, but making them reliable, safe, and scalable - You’re motivated by pushing the frontier of how intelligent systems behave in the real world Compensation $200K – $400K + Offers Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Senior Software Engineer, Agent Platform
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Agent Platform team builds the runtime and model orchestration layer that powers Decagon’s agents in production. This is the orchestration layer that turns workflows, tools and guardrails into a reliable, low-latency, and delightful experience for end users. At the core of this work is the agent harness: the routing, execution logic, tool orchestration, and control-plane systems that determine how an agent behaves in a live conversation. The team owns the full execution lifecycle of each conversation—from selecting workflows and orchestrating multiple models (e.g., router/planner/supervisor patterns), to coordinating tool calls, enforcing safety constraints, and communicating back to the user. The team operates across both real-time systems (e.g., voice interactions with strict latency requirements) and longer-horizon execution (supporting more complex reasoning and workflows). Our research shows that an agent’s task execution reliability increasingly depends on the orchestration layer that wraps around it. This is highly experimental, frontier-style engineering. The team continuously analyzes real-world failures, builds feedback loops through offline evaluation and online experimentation, and iterates quickly to improve quality, reliability, and capability. As model capabilities evolve, the team regularly rethinks system design to push agent performance forward in production. About the Role As a Senior Software Engineer on the Agent Platform team, you will design and build the systems that govern how Decagon agents operate in real-world environments. You will own complex, distributed systems that sit at the heart of the agent runtime: execution frameworks, model orchestration logic, and experimentation platforms that ensure agents are fast, reliable, and continuously improving. Your work will directly impact how agents reason, take actions, and deliver outcomes across millions of interactions. This role operates in a fast-moving, ambiguous space with tight feedback loops. You’ll move fluidly between diagnosing production issues, designing new system abstractions, and running experiments to improve agent behavior. You’ll collaborate closely with Research, Infra, and Product teams to ship improvements safely and at scale. In this role, you will - Design and evolve agent harnesses that power different product experiences - Build core runtime systems, including AOP execution and multi-model orchestration - Develop control-plane logic for routing, planning, and tool invocation with strong safety guarantees - Optimize agent systems for latency, reliability, and production correctness - Analyze real-world failures and use data to drive iterative improvements - Build and operate online experimentation (A/B testing) and contribute to offline evaluation frameworks - Improve observability, testing, and simulation systems to ensure safe, measurable progress - Contribute to voice and real-time systems (e.g., transcription pipelines, turn-taking, latency improvements) - Continuously adapt orchestration systems as model capabilities evolve Your background looks something like this - Strong experience building distributed systems or backend platforms in production environments - Comfort working in ambiguous, fast-moving environments with rapid iteration cycles - Experience owning systems end-to-end, from design through production and iteration - Familiarity with experimentation, evaluation, or data-driven product improvement loops - A track record of improving system reliability, performance, and observability - Ability to debug complex systems and identify root causes of failures Even better - You’ve built or worked on agent harnesses, orchestration layers, or execution frameworks - You think in terms of control planes, feedback loops, and system-level optimization, not just features - You’re excited about diagnosing failure modes and iterating toward measurable improvements - You care deeply about production quality—not just making systems work, but making them reliable, safe, and scalable - You’re motivated by pushing the frontier of how intelligent systems behave in the real world Compensation $200K – $400K + Offers Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Engineering Manager, Research
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Read more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments. Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale. About the Role We’re looking for a manager to lead and grow a team within Decagon Research. You’ll own the team and technical roadmap for an area spanning model post-training, evaluation, safety, speech, or agent behavior, driving ambitious ideas from research to reliable production impact. Managers here operate with high ownership and technical depth while helping their teams move quickly and maintain a high quality bar. You’ll create clarity in ambiguous research areas, develop exceptional engineers, and align the team’s work with the product outcomes that matter most to customers. In this role, you will - Build, manage, and develop a high-performing team of research engineers through hiring, coaching, performance management, and career development - Own the technical direction and roadmap for your area, prioritizing the highest-leverage investments across models, evaluation, safety, speech, and agent systems - Turn open-ended research directions into focused programs with clear hypotheses, milestones, decisions, and measures of production impact - Stay close to the technical work through architecture and experiment reviews, debugging, and individual contribution - Set a high bar for experimental rigor, reproducibility, evaluation quality, engineering execution, and safe model rollouts - Partner across Infrastructure, Agent Platform, Product Engineering, Product, and customer-facing teams to move research into production Your background looks something like this - 5+ years of industry experience building machine-learning systems involving language models, speech, agents, or model infrastructure - 1+ years of people management experience, with a strong individual-contributor background - Deep experience post-training, evaluating, deploying, or serving foundation models at scale - Strong technical judgment and a track record of translating ambiguous research ideas into measurable product outcomes - Experience hiring, coaching, and developing technical talent, with clear communication across research, engineering, product, and executive stakeholders Even better if you have - A record of influential research, open-source contributions, or production ML systems with significant real-world impact Compensation $280K – $430K + Offers Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Engineering Manager, Agent Product
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Agent Product team at Decagon deploys mission-critical AI agents to our customers that impact millions of users and directly drive Decagon’s growth. You will lead a team building on our industry-leading AI agent platform, collaborate directly with customers and help devise long-term, scalable solutions. Our mission is to deliver magical support experiences — AI agents working alongside human agents to help users resolve their issues. About the Role As an Engineering Manager on the Agent Product team, you’ll lead a group of engineers building and shipping best-in-class AI agents, from initial implementation through continuous iteration. You’ll work directly with leaders across industries like finance, healthcare and hospitality, solving their users’ needs with reliable and intuitive AI agents. Managers here are expected to operate with high ownership and technical depth while helping their teams move quickly and maintain a high quality bar. This role is for someone who enjoys mentoring engineers, partnering closely with customers and diving deep into complex system challenges to build elegant solutions that scale to millions of users. In this role, you will - Lead and grow a team of engineers building AI agents that outperform human agents in managing complex customer interactions and driving customer retention - Partner directly with enterprise customers to understand their operational pain points and translate them into scalable AI agent solutions - Drive execution across the full lifecycle of agent deployments, from initial implementation through continuous iteration and optimization - Partner with product, design and research to identify cross-customer trends that guide the evolution of Decagon’s agent platform and research efforts - Help define the technical strategy and roadmap for the future of AI-powered customer support - Support and mentor engineers through technical guidance, feedback and career development - Maintain a high engineering bar while fostering a culture of ownership, velocity and customer obsession Your background looks something like this - Have 1+ years of engineering management experience - Have 5+ years of industry experience in software engineering - Proficiency with Python, Typescript and asynchronous programming - Experience leading teams building complex distributed systems or customer-facing products - A high degree of comfort digging into system failures within deep technology stacks using any tool necessary - Strong communication skills and ability to work directly with enterprise customers Even better - Prior experience working with multi-modal models - Experience leading teams working on AI systems, LLM applications or agentic workflows Compensation $280K – $430K + Equity This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and the scope of responsibilities, with flexibility for candidates who demonstrate exceptional impact. In addition to base salary, we offer competitive equity. Final compensation may vary based on location within the United States. Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Engineering Manager, Agent Orchestration
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team The Agent Orchestration team builds the runtime and model orchestration layer that powers Decagon’s agents in production. This is the orchestration layer that turns workflows, tools and guardrails into a reliable, low-latency, and delightful experience for end users. At the core of this work is the agent harness: the routing, execution logic, tool orchestration, and control-plane systems that determine how an agent behaves in a live conversation. The team owns the full execution lifecycle of each conversation—from selecting workflows and orchestrating multiple models (e.g., router/planner/supervisor patterns), to coordinating tool calls, enforcing safety constraints, and communicating back to the user. The team operates across both real-time systems (e.g., voice interactions with strict latency requirements) and longer-horizon execution (supporting more complex reasoning and workflows). Our research shows that an agent’s task execution reliability increasingly depends on the orchestration layer that wraps around it. This is highly experimental, frontier-style engineering. The team continuously analyzes real-world failures, builds feedback loops through offline evaluation and online experimentation, and iterates quickly to improve quality, reliability, and capability. As model capabilities evolve, the team regularly rethinks system design to push agent performance forward in production. About the Role We’re looking for an Engineering Manager to lead the Agent Orchestration team. This is a highly technical, player/coach leadership role at the core of Decagon’s product. You’ll lead the team responsible for the runtime and control plane that powers every agent interaction—coordinating model reasoning, tool use, and evaluation in production—and own the technical strategy and delivery for the orchestration engine behind every customer conversation. You’ll hire and develop a high-performing team while staying close to architecture, debugging, and reliability. You’ll partner closely with Research, Infrastructure, Product Engineering, and Agent SWE to translate frontier model improvements into predictable, safe, and scalable agent behavior in real customer environments. Success requires strong people leadership, clear execution in ambiguous problem spaces, and the technical depth to drive correctness and operational excellence. In this role, you will - Build, lead, and develop a high performing team of engineers, including hiring, coaching, and performance management. - Own the technical strategy and roadmap for Decagon’s orchestration engine, balancing speed of iteration with correctness and safety. - Drive architecture for systems that coordinate complex reasoning and action flows at scale. - Set reliability, testing, and observability standards across the orchestration stack, and build an operating cadence that prevents repeated incidents. - Create frameworks and guardrails that enable fast, safe iteration on agent behavior, evaluation, and rollout. - Partner with Product, Research, and Infrastructure teams to define requirements, navigate tradeoffs, and ship multi-quarter initiatives that move core company metrics. Your background will look something like this - Have 2+ years of engineering management experience leading high performing teams in fast-moving environments. - Have strong technical depth and an IC foundation that enables you to guide architecture, debug complex failures, and make sound trade-offs. - Have experience building distributed systems, execution engines, real-time platforms, or other high scale systems where correctness and reliability matter. - Have a track record of delivering multi-quarter projects through ambiguity, creating clarity for your team and stakeholders. - Care deeply about engineering craft and operational excellence, including testing strategy, observability, and incident learning. - Communicate clearly and collaborate well across Product, Research, and Infrastructure teams. Even better if you have - Experience with agent frameworks, runtimes, orchestration logic, or tool use systems. - Experience with evaluation, experimentation, or model quality measurement systems. - Experience building guardrails for safety-critical or highly reliable systems. Compensation $280,000 - $430,000 + Offers Equity Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Director of Agent Deployment Engineering
About Decagon Decagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences. Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel. We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others. We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team. About the Team Over the past few years, development of LLMs has evolved at a rapid pace. It’s not enough for our customers to just “set it and forget it” when it comes to AI software. Truly successful AI Agents require hands-on execution, rigorous iteration, and deep technical delivery to reach enterprise-grade performance. We’re creating an Agent Deployment Engineering Org: a specialized technical delivery team responsible for end-to-end execution of AI agent builds. Agent Deployment Engineers own the hands-on work required to deliver best-in-class agents—writing and configuring key components, validating integrations, and ensuring agents perform reliably at scale. This team brings greater specialization and focus to build quality. Agent Deployment Engineers are technical and customer-facing: interfacing with senior technical stakeholders while going deep on agent configuration and build execution. About the Role As Director of Agent Deployment Engineering, you will lead Decagon’s technical delivery for strategic enterprise customers—owning outcomes across multiple deployments and building the team, playbooks, and operating system required to scale. This is a senior, customer-facing leadership role where you’ll partner with customer executives and technical leaders to define success, translate requirements into delivery plans, and drive launches that measurably impact customer outcomes. You’ll work closely with Agent PMs, Agent Success, Engineering, and GTM leadership to create tight feedback loops: driving delivery, surfacing product gaps, and influencing the evolution of Decagon’s agent-building platform based on real enterprise needs. This role is ideal for a leader who thrives in fast-moving environments, enjoys shipping customer-facing technical work, and can balance hands-on problem solving with structured execution at scale. In this role, you will - Lead and scale a high-performing delivery org - Own end-to-end execution of AI agent deployments for enterprise customers across a portfolio, from scoping through launch and iteration. - Build, lead, and develop a team of Agent Builders; hire, coach, and set a high bar for quality, velocity, and customer outcomes. - Establish delivery operating rhythms (planning, reviews, retros), capacity planning, and forecasting to ensure predictable execution. - Drive executive-level customer engagements - Interface with senior technical stakeholders and executives to define success criteria, align on constraints (security/compliance), and drive delivery against timelines. - Lead complex escalations and unblock cross-functional teams when quality, timelines, or customer outcomes are at risk. - Translate customer needs into crisp internal documentation and execution plans across Product/Engineering/GTM. - Create repeatable playbooks and scale mechanisms - Define and standardize delivery methodologies and artifacts (e.g., AOP quality bar, launch readiness checklists, iteration loops). - Establish best practices for evaluation and guardrails to ensure safe, compliant, and predictable agent performance in real-world scenarios. - Improve tooling and processes to reduce time-to-launch and increase reliability across deployments. - Influence the platform roadmap through deployment insights - Identify recurring product/platform gaps and drive prioritization with Engineering and Product leadership. - Partner with internal teams to turn real customer needs into platform improvements that compound across deployments. Your background looks something like this - 10+ years of relevant experience in technical, customer-facing roles (e.g., forward-deployed engineering, solutions engineering, technical consulting, implementation engineering, technical product/PM, or similar). - 5+ years of people management experience, including hiring, coaching, performance management, and building high-performing teams; ideally experience leading senior ICs and/or managers. - Strong technical foundation—comfortable working with APIs, integrations, and complex systems; able to go deep to diagnose issues and guide solution architecture. - Experience delivering production-grade customer solutions that require structured execution, testing/validation, and iteration. - Ability to communicate clearly with senior technical stakeholders, translate requirements into execution plans, and drive delivery. - Comfort operating in fast-moving, ambiguous environments where you build structure while maintaining momentum. Even better if you have - Experience deploying LLM-based products or AI agents in production (prompting, evaluation, guardrails, tooling, workflow design). - Experience with enterprise SaaS integrations (e.g., ticketing systems, CRM, data pipelines) and security/compliance considerations. - Strong product instincts—ability to define success metrics, write crisp requirements, and contribute customer insight back into product roadmap. - Experience scaling a delivery function from high-touch execution to repeatable playbooks and durable operating cadence. Compensation $250K – $320K + Offers Equity Benefits We proudly offer the following benefits for our full-time employees: - Medical, Dental, and Vision benefits for you and your family - Life Insurance and Disability Benefits - Retirement Plan (e.g., 401K, pension) - Parental Leave - Fertility and family building benefits through Carrot - Monthly stipend to support your wellness, lifestyle, and work-life balance - Daily lunches and snacks in the office to keep you at your best - Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave) These benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.
Sr Technical Account Manager - East
Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack - empowering organizations to run AI across multi-vendor environments with centralized governance. The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog , LinkedIn , X , and YouTube . Technical Account Managers are highly experienced Architects who are comfortable with a very client facing role and who dedicate themselves to a small set of strategic clients, (~4 per TAM). They must be quick on their feet and able to put a positive spin on challenging customer situations, both in the boardroom with a client CTO and while sharing the command line with a client admin. They must be effective technically, both as communicators and doers. They must be capable of managing and maintaining a client relationship, while keeping a tight organizational watch over the technical aspects of their accounts. How you'll make an impact - Work with the Customer Success team and customers to jointly identify near and longer-term priorities and define the associated engagement plan - Manage milestones with Customer Success Manager and customer and contribute to deliverables, provide regular status updates and proactively identify and mitigate issues/risks - Centralize the technical information about clients and take part to the account strategy and with the other members of the account team - Play an active role contributing to the growth and scalability of the Field Engineering team through robust documentation, continuous process optimization, and peers upskilling - Work with Customer resources as a primary technical advisor, providing guidance and hands-on support on the following matters: Dataiku platform architecture (initial deployment, expansions), platform operations (upgrades), best practice related to Dataiku usage, security, data management, compute resources, ML-Ops, Monitoring, etc. - Help clients troubleshoot the implementation of the product within their systems. - Ensure that feature requests are effectively recorded and communicated to product and R&D - Advise client tech leaders on choices around new companion technologies and tech strategies around Dataiku - Support innovative approaches around Dataiku (edge computing, deep learning, advanced MLOps, for example) What you'll need to be successful - 7+ years of experience in a customer facing technical role - Comfort and confidence in client-facing interactions - Ability to work both pre and post sale - Strong Linux system administration experience including networking - Experience with authentication and authorization systems like LDAP, Kerberos, AD, and IAM - Hands-on experience with cloud based services like AWS, Azure and GCP - Hands-on experience with the Kubernetes ecosystem for setup, administration, troubleshooting and tuning - Experience with the Hadoop and/or Spark ecosystem for setup, administration, troubleshooting and tuning How you'll stand out - Experience with Python - Some knowledge of Java, nice to have - Some knowledge in ML Ops What does the hiring process look like? #LI-Remote #LI-AN1 - Initial call with a member of our Technical Recruiting team - Video call with the the USA TAM Director - Technical Assessment to show your skills (Home Test) - Debrief of your Tech Assessment with TAM Team members - Final Interview with the Global VP of Field Engineering Compensation and Benefits The final compensation package for this role will be determined during the interview process and is based on a variety of factors, including, but not limited to, geographic location, internal equity, education, skill set, experience and training. Eligible roles may also be entitled to receive commission or other variable compensation through Dataiku's incentive compensation program. Dataiku also offers comprehensive benefits, including stock options, medical, dental, and vision plans, flexible spending accounts, pre-tax commuter benefits, a 401k company match, paid vacations and sick leave, paid parental leave, employer paid disability coverage, and additional health and wellbeing perks and benefits. Dataiku reserves the right to amend or modify employee perks and benefits at any time. US only national base pay ranges $150,000 - $200,000 USD What are you waiting for! At Dataiku, you'll be part of a journey to shape the ever-evolving world of AI. We're not just building a product; we're crafting the future of AI. If you're ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can't wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page . Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com Protect yourself from fraudulent recruitment activity Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.
Staff Software Engineer, Ads Measurement & Orchest...
P-1607 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. Enterprises spend more than $700 billion on digital advertising, however for the most part, they have very little data & intelligence on how their campaigns are performing. Reconciling that is slow, manual, and mostly wrong, and optimizing those campaigns historically has involved humans and agencies. We are building the data and agent layer underneath that problem, and we are looking for an engineer to help lead that effort. The impact you'll have: - Lead the ingest and normalization path for advertising platform data at scale, including rate limits, schema drift, backfills, and restated numbers - Design the aggregation and identity layers that make figures from different platforms comparable - Lead development of agentic workflows that parse performance data, interpret it, present it, and act on it - Set the correctness and evaluation bar in a domain where ground truth is noisy and partially observable - Partner closely with product management, design, and other engineering teams to build intuitive, scalable, and extensible solutions that drive user & business growth What we look for: - 10+ years of engineering experience, including time as a tech lead or leading other tech leads, on complex enterprise software projects - Hands-on experience with walled garden advertising APIs (Meta, Google, Amazon, TikTok) or the equivalent from the advertiser, agency, or DSP side - Working knowledge of ad tech data models: campaign hierarchies, attribution windows, conversion APIs, deduplication across sources - Familiarity with measurement approaches such as MTA, MMM, incrementality testing, and privacy-preserving aggregation - Experience shipping LLM-powered systems to production, including evaluation and guardrails - High ownership and bias for action in 0→1 environments: you are comfortable making pragmatic trade-offs, operating with incomplete information, and driving projects from idea through launch and adoption - Strong ability to collaborate across product, engineering, and design teams to align technical strategy with company growth objectives - Combination of technical and people leadership, for example, as a TLM (Nice to have) - Built or operated measurement infrastructure at a platform, measurement vendor, or large advertiser (Nice to have) - Background in experimentation or causal inference (Nice to have) Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Local Pay Range $190,900 - $253,750 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Staff Software Engineer - Search Platform
P-375 The Search team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking a Staff Engineer to lead enhancements to our Search Quality. We are focusing on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities - Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. - Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. - Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. - Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For - BS+ (M.S. or PhD preferred) in Computer Science, or a related field. - 10+ years experience developing search relevance systems at scale in production or in high-impact research environments. - Experience applying LLM to search relevance - Experience in one or more of the following: - Query understanding - NLP - Text mining - Recommendations - Personalization - Discovery - Conversational AI - Strong understanding of computer science fundamentals. - Contributions to well-used open-source projects. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts. If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you! About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Staff Forward Deployed Engineer
CSQ427R243 As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - 6+ years experience in data engineering, data platforms & analytics, or software engineering - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployments - Working knowledge of MLOps, ML/AI models and AI APIs - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Staff Designated Support Engineer
CSQ227R215 As a Staff Designated Engineer and tech subject matter expert, you will partner closely with our Field and Engineering teams to deliver high-touch specialised support and tailored technical solutions for Databricks' largest and most strategic customers in the Digital Native Business (DNB) segment. In this customer-facing role, you will leverage your technical expertise in Apache Spark™ and other data technologies to triage and resolve complex product issues and unblock our customers’ most critical technical challenges. The Impact You Will Have: - Perform advanced Troubleshooting and Root Cause Analysis to resolve performance and reliability issues in Spark, SQL, Delta, Streaming, and Databricks runtime features using tools like Spark UI metrics, Mosaic AI Model Service, DAGs, and event logs. - Discover requirements for continuous monitoring to detect early performance issues, working with R&D and NOC teams to optimise the DNB customer environments. - Build Rapid POCs, Test/Deploy/Monitor the solutions built by Databricks Engineering to address customer challenges and showcase advanced Spark/ML/AI runtime capabilities aligned with their business goals. - Develop comprehensive playbooks and maintain a knowledge base of common issues and solutions for Spark, ML, and AI workflows. - Train customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks Features. - Pilot new best practices processes/ programs, champion process improvements, and collaborate with cross-functional teams to enhance the customer experience. - Advocate for customers in business review meetings and maintain close relationships as a trusted advisor and primary technical point of contact. - Collaborate onsite with Field Engineering, Sales, and Product teams during customer engagements and technical presentations to provide rapid solutions to production-impacting issues, demonstrating deep technical expertise and building strong customer trust. What We Look For: - Technical Expertise in Big Data and Spark: 10+ years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala. - Data Engineering Specialisation: Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, Bigquery, etc - Advanced Tech Skills : Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimisation, and memory management, with additional proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI. - Cloud and CI/CD Skills: Practical experience with AWS, Azure, or GCP, coupled with expertise in building and managing CI/CD pipelines, monitoring, and alerting systems. - Customer-Facing Experience: 3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving skills. - Advanced Proactive Problem Solving Skills : Proven ability to anticipate, identify, and mitigate risks while planning solutions for production challenges. Effectively use sound business judgment, risk avoidance and subject matter expert resources to coordinate team efforts to solve problems. - Collaboration and Leadership: Proven ability to work with cross-functional teams and senior leadership to address roadblocks, mitigate risks, and drive customer success while creating impactful documentation for self-service solutions. About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Solutions Engineer - Digital Native Business (...
The Role As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage within Digital Native customers. The Impact You Will Have - Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning - Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins - Own frontline technical relationships with customer engineers, data teams, and technical leads - Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption - Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations - Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community What We Look For - 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role - Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage - Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP) - Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink) - Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews - Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics - Strong presentation and demo skills — you will build and present a live solution during the interview - Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience) Nice to Have: - Databricks certification or experience with the Databricks Platform - Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow - Background at a data/AI company, cloud provider, or technical consulting firm Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Local Pay Range $152,300 - $209,450 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Solutions Engineer
Req: FEQ427R137 Location: Singapore The Role As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage. The Impact You Will Have - Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning - Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins - Own frontline technical relationships with customer engineers, data teams, and technical leads - Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption - Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations - Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community What We Look For - 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role - Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage - Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP) - Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink) - Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews - Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics - Strong presentation and demo skills — you will build and present a live solution during the interview - Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience) Nice to Have: - Databricks certification or experience with the Databricks Platform - Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow - Background at a data/AI company, cloud provider, or technical consulting firm Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Industry Marketing Manager, Startups
MKTQ427R40 We are looking for a creative, passionate and well-rounded individual to join our Digital Native and Startup marketing team to help us focus on the fastest-moving segment in tech: venture-backed startups building and scaling on AI. Our mission is to meet founders and technical teams where they are, from pre-seed to pre-IPO, with messaging, programs and community that make Databricks the obvious foundation for the companies being built right now. This is a highly collaborative strategic role that works closely with many other functions, plus the venture capital ecosystem that surrounds this segment. As a Sr. Industry Marketing Manager at Databricks, you will guide messaging, content and GTM programs for the Startup segment. You will work with sales, partners, VCs, accelerators and our customers to build awareness, demand generation and sales enablement programs that help achieve pipeline goals. You will also build the credibility engine for this audience through founder and engineering-led content, developer channels, community programs, and startup and investor events. This role reports to the Sr. Director of Industry Solutions Marketing. Ideal candidates will have a proven record of impact marketing to startups and developers, real technical fluency, and a working understanding of how venture-backed companies buy, adopt and expand their use of infrastructure and AI tooling. You will have a strong point of view on where this segment is going, informed by time spent with founders, investors and builders. Finally, you will have experience building strategies that resonate with a startup audience, from the first engineer evaluating a platform to the founder or CTO signing off on the spend. The impact you will have - Establish a startup-segment positioning and content framework used consistently across priority sales, partner, developer, field, and demand-generation programs, with adoption measured through program usage and stakeholder feedback. - Meet or exceed agreed pipeline and consumption targets for priority startup accounts through integrated account-based, partner, venture, demand-generation, and field programs. - Build an active venture and accelerator ecosystem that generates measurable portfolio reach, co-marketing activity, qualified opportunities, and sourced or influenced pipeline. - Improve the conversion of startup evaluations into committed production spend by optimizing credits, trials, free-tier, and other product-led motions, measured through activation, conversion, and expansion rates. - Increase awareness and technical credibility with startup founders, developers, and technical leaders, measured through target-audience engagement, community participation, content-assisted opportunities, and event outcomes. - Equip go-to-market teams with startup-specific messaging, technical proof points, sales plays, and enablement that improve seller adoption and segment performance, including conversion, win rate, or sales-cycle metrics. - Expand the segment’s customer and community proof through credible startup stories, technical content, speaking engagements, and investor or developer events that contribute to reach, engagement, and pipeline. What we look for - 7+ years of experience marketing technology to startups, developers, or the venture ecosystem, or equivalent experience building and scaling a venture-backed startup. - A proven record of owning marketing strategy for a segment, product line, or go-to-market motion and delivering measurable pipeline, adoption, consumption, or revenue outcomes. - Experience developing positioning, messaging, and content for complex technical B2B products and translating cloud, data, analytics, or AI/ML capabilities into clear customer use cases and business outcomes. - Technical fluency in modern data and AI architectures, including the technologies and buying considerations relevant to model providers, agent frameworks, vector search, evaluation tooling, and production workloads. - Demonstrated success building relationships with venture firms, accelerators, incubators, startup communities, customers, or strategic partners to drive awareness, co-marketing, adoption, or pipeline. - Working knowledge of venture-backed company buying dynamics, including funding stages, budget and runway pressures, buying authority, and triggers that accelerate or stop infrastructure and AI platform decisions. - Experience with product-led and consumption-based growth motions, including self-serve funnels, trials, credits, free tiers, and the path from technical evaluation to committed spend. - Experience leading cross-functional programs and presenting credibly to founders, technical leaders, investors, sales teams, and partners while balancing strategic direction with fast, hands-on execution. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $163,400 - $224,750 USD Zone 2 Pay Range $147,100 - $202,300 USD Zone 3 Pay Range $139,000 - $191,050 USD Zone 4 Pay Range $130,700 - $179,750 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Forward Deployed Engineer (FDE) - Public Secto...
CSQ427R187 PLEASE NOTE: Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply. About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role As a Sr. Forward Deployed Engineer (FDE), you will work with federal government customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. Please note: this role is hybrid and has a requirement to travel to customer locations 20-25% of the time The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Deliver Technical Components: Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs - Cross-Collaborate: Work with Engineers and Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What We're Looking For: Minimum Qualifications: - 6+ years experience in data engineering, data platforms & analytics, or software engineering - Fluency in writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with PySpark, Apache Spark™ and knowledge of Spark runtime internals - Experience with CI/CD for production deploymentsWorking knowledge of MLOps, ML/AI models and AI APIsDesign and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces - Experience with technical project delivery, documentation and white-boarding skillsExperience working with enterprise clients and managing conflicts across a broad stakeholder range Preferred Qualifications: - 10+ years experience in data transformation and warehousing within enterprise level, distributed data systems - Expertise in MLOps, ML/AI models, and AI APIs - Certification in a Databricks-specific domain Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $182,000 - $250,208 USD Zone 2 Pay Range $182,000 - $250,208 USD Zone 3 Pay Range $182,000 - $250,208 USD Zone 4 Pay Range $182,000 - $250,208 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Forward Deployed Engineer (FDE) - Public Secto...
CSQ327R224 *This role requires an active Secret or Top Secret clearance* About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role As a Sr. Forward Deployed Engineer (FDE), you will work with federal government customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. Please note: this role is hybrid and has a requirement to travel to customer locations 20-25% of the time The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Deliver Technical Components: Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs - Cross-Collaborate: Work with Engineers and Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What We're Looking For: Minimum Qualifications: - 6+ years experience in data engineering, data platforms & analytics, or software engineering - Fluency in writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deploymentsWorking knowledge of MLOps, ML/AI models and AI APIsDesign and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces - Experience with technical project delivery, documentation and white-boarding skillsExperience working with enterprise clients and managing conflicts across a broad stakeholder range Preferred Qualifications: - Expertise in MLOps, ML/AI models, and AI APIs - Databricks Certification Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $182,000 - $250,208 USD Zone 2 Pay Range $182,000 - $250,208 USD Zone 3 Pay Range $182,000 - $250,208 USD Zone 4 Pay Range $182,000 - $250,208 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Forward Deployed Engineer (FDE) - Digital Nati...
CSQ227R258 As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks Platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get the most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specifications with exceptional customer empathy. Location: San Francisco Bay Area Preferred This role is San Francisco Bay Area-focused. We're looking for someone who is based in the San Francisco Bay Area, willing to relocate or able to travel to the area at least one week per month to spend meaningful time with customers and the team. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - 6+ years of experience in data engineering, data platforms & analytics, or software engineering - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployments - Working knowledge of MLOps, ML/AI models and AI APIs - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Local Pay Range $182,000 - $250,208 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Forward Deployed Engineer - National Security
ADD REQ ID CSQ427R88 PLEASE NOTE: Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. Candidates with an active Secret or higher clearance are strongly encouraged to apply. About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems, from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, and customer obsessed, we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role As a Sr. Forward Deployed Engineer (FDE), you will work with federal government customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. Please note: this role is hybrid and has a requirement to travel to customer locations 20-25% of the time The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Deliver Technical Components: Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs - Cross-Collaborate: Work with Engineers and Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What We're Looking For: Minimum Qualifications: - 6+ years experience in data engineering, data platforms & analytics, or software engineering - Fluency in writing code in Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deploymentsWorking knowledge of MLOps, ML/AI models and AI APIsDesign and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces - Experience with technical project delivery, documentation and white-boarding skillsExperience working with enterprise clients and managing conflicts across a broad stakeholder range Preferred Qualifications: - Expertise in MLOps, ML/AI models, and AI APIs - Databricks Certification Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $182,000 - $250,208 USD Zone 2 Pay Range $182,000 - $250,208 USD Zone 3 Pay Range $182,000 - $250,208 USD Zone 4 Pay Range $182,000 - $250,208 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr. Forward Deployed Engineer
Req ID: CSQ427R251 Location: Tokyo, Japan As a Sr. Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - 10+ years experience in data engineering, data platforms & analytics, or software engineering - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployments - Working knowledge of MLOps, ML/AI models and AI APIs - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification - Fluent in Japanese with a professional working proficiency in English About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr Full Stack Developer (AI Agents)
GAQ226R75 About the Role We are looking for a Senior Full Stack Developer to design, build, and deploy modern, scalable AI agents and applications that leverage Large Language Models (LLMs). This role requires a strong focus on end-to-end agent development, including building a high-performance React frontend, designing the agentic logic in Python, integrating with backend services, and ensuring production readiness. Key Responsibilities: - Design, develop, and deploy AI agents for business-critical workflows, with a focus on LLM orchestration and tooling. - Implement complex agentic behaviours using frameworks like LangChain or LangGraph, including ReAct loops for reasoning and action. - Design and develop a high-performance React application for the agent's user interface. - Collaborate with backend teams to integrate APIs and services, and build tools for agents. - Work with middleware (Python/Node.js) to orchestrate agent calls and data flow. - Implement comprehensive observability and tracing for agent runs and system performance. - Build reusable, scalable UI components. - Optimise application performance, responsiveness, and scalability. - Participate in architectural discussions and contribute to solution design. - Write clean, maintainable, and testable code with proper documentation. Required Skills & Experience - 5+ years of experience in full-stack development, with strong expertise in Python and React.js . - Proven experience in designing, building, and deploying at least 1 production-deployed AI agent or LLM application . - Deep expertise in LLM orchestration, prompt engineering, and utilizing tools/plugins to extend agent capabilities. - Experience with agent frameworks like LangChain or LangGraph , including implementing reasoning patterns like the ReAct loop . - Experience with observability, logging, and tracing for AI agents. - Experience building large-scale, enterprise-grade applications. - Strong experience with API integration (REST/GraphQL). - Experience working in Agile/Scrum environments. - Strong problem-solving and system design skills - Ability to work across frontend and backend integration layers - Ownership mindset with attention to detail - Good communication and collaboration skills Preferred / Good to Have - Experience with Node.js or Python for middleware development - Understanding of Salesforce APIs (REST, Apex, RLM/CPQ) - Experience with event-driven architectures (webhooks, CDC, async processing) - Knowledge of CI/CD pipelines and DevOps practices - Experience with Databricks platform and Mosaic AI About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Software Engineer - Search
P-926 The Applied AI team at Databricks sits at the forefront of advancing AI/ML-powered products. Databricks’ customers are continuously creating new assets (tables, notebooks, dashboards, datarooms, pipelines, sql queries, ml models etc.) on the platform. Finding an asset is a critical user journey for Databricks’ customers which helps them accomplish their tasks. As our Search product continues to evolve, we are seeking multiple senior engineers to drive enhancements to our Search Quality. In 2026, we will focus on enhancing search ranking, improving query understanding, building robust evals and growing the coverage of assets to enable seamless search at scale. Key Responsibilities - Drive the development and deployment of ML based search and discovery relevance models and systems integrated with Databricks' products and services. - Design and implement automated ML and NLP pipelines for data preprocessing, query understanding and rewrite, ranking and retrieval, and model evaluation, enabling rapid experimentation and iteration. - Collaborate with product managers and cross-functional teams to drive technology-first initiatives that enable novel business strategies and product roadmaps for the search and discovery experience. - Contribute to building a robust framework for evaluating search ranking improvements - both offline and online. What We’re Looking For - BS+ (M.S. or PhD preferred) in Computer Science, or a related field. - 5+ years experience developing search relevance systems at scale in production or in high-impact research environments. - Experience applying LLM to search relevance - Experience in one or more of the following: - Query understanding - NLP - Text mining - Recommendations - Personalization - Discovery - Conversational AI - Strong understanding of computer science fundamentals. - Contributions to well-used open-source projects. Why Join Us? At Databricks, we are building state-of-the-art AI solutions that redefine how users interact with data and our products. You’ll have the opportunity to shape the future of AI-driven products at Databricks, work with cutting-edge models, and collaborate with a world-class team of AI and ML experts. If you're excited about pushing the boundaries of AI in real-world applications, we’d love to hear from you! About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Forward Deployed Engineer (Technical Data A...
Req ID: CSQ427R156 Location: London, United Kingdom - Hybrid Job Role: Senior Forward Deployed Engineer - Technical Architect level Recruiter: Dina Hussain We’re hiring for multiple roles within our FDE team. As a Forward Deployed Engineer (FDE), you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get the most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specifications with exceptional customer empathy. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects, including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects that lead to a customer's successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customers' needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement-specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - Experience in data engineering, data platforms & analytics, or software engineering / full stack development - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployments - Working knowledge of MLOps, ML/AI models and AI APIs - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification - an advantage About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Senior Forward Deployed Engineer
CSQ427R228 As a Senior Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - - 6+ years of experience in data engineering, AI, data platforms & analytics - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Working knowledge of MLOps, ML/AI models and AI APIs - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployment - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Forward Deployed Engineering - Senior Architect
As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - Strong years experience in data engineering, data platforms & analytics, or software engineering - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployments - Working knowledge of MLOps, ML/AI models and AI APIs - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification preferred but not essential About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Forward Deployed Engineer
Req ID: CSQ427R277 Location: Tokyo, Japan As a Forward Deployed Engineer (FDE) you will work with customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will own the architecture, lead design decisions, and implement end-to-end systems spanning data engineering, AI, and application development. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy. The impact you will have: - Production Solution Delivery: Lead impactful customer technical projects by delivering production-grade systems, designing and building reference architectures, custom applications and data ingestion and ML/AI model integration - Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer - Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. - Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices. - Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs. - Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues. - Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact. - Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap. What we look for: - 8+ years experience in data engineering, data platforms & analytics, or software engineering - Comfortable writing code in either Python, Scala, JavaScript/TypeScript, and modern frameworks - Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one - Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals - Familiarity with CI/CD for production deployments - Working knowledge of MLOps, ML/AI models and AI APIs - Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces. - Experience with technical project delivery - managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions. - Documentation and white-boarding skills. - Experience working with enterprise clients and managing conflicts across a broad stakeholder range - Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects. - Travel to customers 20% of the time - Databricks Certification - Fluent in Japanese with a professional working proficiency in English About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Director, Marketing Strategy and AI Transformation
SLSQ427R391 Location: United States, Remote [San Francisco Bay Area Preferred] Databricks is seeking a Director, Marketing Strategy and AI Transformation to own how our global marketing organization decides where to invest and reimagine how the work gets done. This role brings annual planning and investment strategy together with the redesign of marketing workflows for an AI and agentic operating model. You will set the planning and investment operating model for marketing while leading the shift from human-executed to agent-executed work across the organization. This highly cross-functional role partners closely with Marketing Leadership and their departments, Finance, Sales Strategy and our central platform and data teams to make investment decisions that are grounded in real capacity and to turn AI capability into standard practice at scale. Reporting to the AVP of Marketing Technology, Data, and Growth, you will build and lead a net-new team, establishing this function from the ground up. The impact you will have: - Own the end-to-end annual marketing planning process, establishing a single planning system of record with explicit trade-offs - Evaluate leading indicators and business outcomes to understand low and high performance areas and drivers - Identify and scale best practices to drive incremental growth across global business units - Build and maintain the marketing capacity model spanning people, agencies, and agent-based execution, so that commitments are made against known capacity constraints - Oversee development of the highest-leverage marketing workflows for agent execution, targeting a step-change improvement in time-to-market - Align marketing investment strategy against the company's strategic bets, ensuring clarity on spend and capacity toward the highest-impact products and programs, and improving pipeline efficiency. - Drive marketing target setting in partnership with Marketing, Finance and Sales Strategy, establishing a transparent methodology which can shift agilely with the business - Drive agent adoption across the global marketing organization and establish org-wide standards for prompts, context, and agent workflows, measured by sustained change in time to market. - Establish AI governance and adoption guardrails for agent-based marketing, setting standards for quality, risk, data privacy, and responsible use, so that adoption scales safely and consistently. - Build and develop a high-performing team from the ground up, and model and reinforce Databricks' culture principles. What we look for: - Deep experience in marketing strategy, marketing planning, marketing operations, or GTM/revenue operations in a B2B environment within SaaS or enterprise technology, including ownership of an annual planning or investment allocation cycle at scale. - Demonstrated experience redesigning workflows around AI, including hands-on work building agent workflows, writing and iterating prompts, and structuring context - Track record of driving sustained behavior change across a large, matrixed organization, with evidence that adoption persisted beyond the initial rollout. - Expertise in how a marketing organization operates end to end across demand generation, campaign operations, content production, field and events, brand, and analytics - Strong understanding of full-funnel marketing measurement and how marketing investment connects to pipeline and revenue, ideally in a consumption or usage-based business model. - Familiarity with the enterprise marketing stack including marketing automation, CRM, CDP, orchestration, and BI, and with modern agent frameworks and MCP-based integrations. Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $221,800 - $305,050 USD Zone 2 Pay Range $199,700 - $274,550 USD Zone 3 Pay Range $188,600 - $259,250 USD Zone 4 Pay Range $177,400 - $244,000 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Customer Enablement Architect (Capability Engineer...
CSQ427R440 The Databricks Customer Enablement team is on a mission to upskill data and AI professionals in customer organizations so they can use Databricks effectively and accelerate customer success. As a Customer Enablement Architect, you will design and lead customer enablement and talent-transformation programs across Australia and New Zealand. You will partner with Sales, Field Engineering, Forward Deployed Engineering, Training Delivery, and Operations to understand customer needs, recommend the right learning solutions, and ensure successful execution. You will balance strategic customer engagement with program and commercial execution across training bookings, revenue, learners, credentials, and adoption. You will bring enough technical depth to understand Databricks curriculum and certifications, make credible recommendations, and engage confidently with technical stakeholders—without being expected to deliver deep hands-on technical training. The impact you will have - Work with regional Go-to-Market teams to create enablement strategies aligned to customer segment, business priorities, technical maturity, and talent-transformation goals. - Translate customer outcomes into practical learning plans, capability roadmaps, and recommendations across free and paid training, instructor-led and self-paced learning, credentials, and partner delivery. - Partner with global Delivery and Operations teams to coordinate scheduling, communications, program quality, and seamless execution of customer development plans. - Manage and report weekly, monthly, and quarterly performance across training bookings, revenue, learners, credentials, and adoption; use insights to guide action from field teams. - Serve as the voice of the customer for regional enablement, curriculum, and certification priorities, while engaging senior leaders and executives internally and externally. - Identify capability gaps that may affect platform adoption and work with account teams on targeted interventions, including contextual or just-in-time enablement where it improves customer outcomes. Technical context you will support You will help customers build capability across areas such as: - Lakehouse architecture, data engineering, ETL, data governance, and data quality - Databricks training, certifications, and foundational onboarding experiences - Generative AI, agentic workflows, Databricks Apps, Genie, and Lakeflow - Translating technical adoption needs into accessible enablement and talent-transformation programs You do not need to be a principal engineer. You should be able to hold a credible technical conversation, understand curriculum and certification requirements, and recommend the right enablement path. Experience creating a prototype, automation, or technical tool is valuable but not required. What we look for - 5+ years of demonstrated experience in Customer Enablement, Talent Transformation, Training, Customer Success, Consulting, or managing a book of business. - Hands-on Builder Mindset: A non-negotiable track record of personally designing, building, and deploying working prototypes, automation tools, or technical apps. - Experience creating and leading enablement programs in partnership with Sales and technical teams to deliver customer outcomes. - Experience in Big Data, AI, Data Science, cloud platforms, or enterprise technology, with the ability to understand technical curricula and certifications. - Strong customer and executive engagement skills, including discovery, stakeholder management, presentation, facilitation, and navigating ambiguity. - Commercial & Business Insight: Ability to connect technical skill outcomes to core P&L levers, influence renewals/expansions, and collaborate effectively with sales on strategic account planning. - Experience operating across ANZ markets, strong operational discipline, and willingness to travel as needed - Experience with technical solutioning or building tools is a plus. About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Sr Staff Site Reliability Engineer, AI Infrastruct...
At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution. Ready to come find your playground? Together, we can help shape the endless possibilities of AI. Role Overview d-Matrix's SRE team owns the infrastructure layer that every engineering team and customer depends on — colocation facilities, on-premises GPU clusters, cloud environments, and the platform services used to deploy and validate d-Matrix hardware and software. This role is a core member of that team, responsible for reliability, automation, and observability across colo, on-premises lab, and cloud environments. You will own systems end-to-end, from provisioning through live incident response, partnering with hardware and software teams on CI/CD, QA, and HPC workloads for silicon development, as well as supporting customer-facing environments where d-Matrix partners collaborate on deployments. This is hands-on, high-ownership work: you'll build and operate real infrastructure, not manage tickets. What You Will Do - Own reliability and availability across colo server fleets, on-premises lab clusters, cloud environments (AWS, Azure, GCP), and customer-facing platform services. - Perform hands-on infrastructure work — server provisioning, OS configuration, networking, storage, and hardware troubleshooting — from bare metal through auto-scaling Kubernetes environments. - Lead capacity planning and hardware lifecycle management for your domains, and track cloud spend to support FinOps and workload placement decisions. - Drive all provisioning, deployment, and operational changes through Terraform and/or Ansible rather than manual steps, and contribute to shared IaC modules used across the global SRE and data center services teams. - Build and document automation that eliminates toil — host lifecycle management, fleet health checks, auto-remediation, self-service tooling, and networking automation for cluster interconnects and lab configurations. - Design and maintain monitoring, alerting, and SLIs (Prometheus/Grafana, DataDog, Splunk, or equivalent), contributing to AIOps-driven detection workflows. - Participate in on-call rotation, triaging and resolving incidents from bare metal to application layer, and produce high-quality RCAs for P0/P1 incidents. - Support platform services used by internal teams and external customers, ensuring QoS and uptime commitments and documenting operational runbooks. What You Will Bring - Bachelor's or Master's in Computer Science, Electrical Engineering, or a related field (or equivalent experience); 7+ years in SRE, infrastructure engineering, or systems administration. - Strong Linux systems knowledge with hands-on colocation or on-premises server infrastructure — networking, storage, systemd, kernel parameters, performance diagnostics, physical hardware, rack networking, and bare-metal provisioning. - Production IaC experience with Terraform and/or Ansible — writing and maintaining configurations, not just running existing playbooks. - Kubernetes operational experience: cluster troubleshooting, workload management, storage, and networking. - Experience with observability tooling — Prometheus/Grafana, DataDog, Splunk, or equivalent — including building dashboards and writing alert rules. - Production-quality Python and/or Bash scripting, paired with incident response experience: structured triage, RCA production, and follow-through on action items. Preferred Qualifications - Experience operating customer-facing infrastructure or platform services with external reliability expectations. - Cloud infrastructure operations across AWS, Azure, or GCP, including hybrid environments spanning cloud and on-prem. - Experience deploying and operating AI-driven infrastructure tools — AIOps platforms, intelligent alerting, anomaly detection, or LLM-assisted diagnostics — in production. - HPC job scheduler experience: Slurm, LSF, or equivalent. - Knowledge of high-speed interconnect fabrics: InfiniBand, RoCE, or NVLink. - Experience with large-scale infrastructure automation — host lifecycle management, fleet auto-healing, or AIOps-driven operations — building tooling that reduces manual intervention, not just running it. Equal Opportunity Employment Policy d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day. d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.
Director Site Reliability Engineer, AI Infrastruct...
At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution. Ready to come find your playground? Together, we can help shape the endless possibilities of AI. Role Overview d-Matrix designs and manufactures purpose-built AI inference silicon, and the infrastructure underpinning our engineering organization must be as reliable and scalable as the chips we build. This role builds and leads d-Matrix's Site Reliability Engineering function from the ground up, owning the infrastructure that development, validation, and customer-facing deployments run on — spanning colocation facilities, on-premises lab clusters, cloud environments (AWS, Azure, GCP), and customer-facing platform services. You will hire and grow the team, set technical direction, own SLOs for critical systems, and serve as the senior escalation point for incidents, all while remaining hands-on. You will partner closely with Software Tools, QA DevOps, and Engineering teams whose workflows run on this infrastructure, as well as Networking Operations and IT Operations, to drive reliability, cost efficiency, and the removal of technical debt. What You Will Do - Build and lead the SRE function from scratch — define its charter, establish SRE as a discipline across hardware and software engineering, and hire, develop, and retain a team of 1–3 SRE engineers. - Direct a dedicated Data Center & Lab Technician team, setting work priorities and operational standards across on-premises and colocation facilities. - Own 24×7 reliability across colocation, on-premises lab clusters, cloud, and customer-facing platform services, designing for failure domains, progressive delivery, and strict change control. - Establish SRE process from zero: define SLIs/SLOs and error budgets, design on-call rotations (including a follow-the-sun model as d-Matrix expands globally), and build the incident and RCA management framework. - Own the full observability stack (Prometheus, Grafana, Datadog, Splunk or equivalent), instrumenting metrics, traces, and logs for SLO visibility and alert design. - Drive IaC-first automation (Terraform, Ansible) and build self-healing infrastructure — host lifecycle automation, fleet auto-remediation, and AIOps-driven alerting. - Own FinOps and capacity planning across cloud, colocation, and on-premises tiers, including spend attribution, TCO modeling, and workload placement decisions. - Lead the migration from ad-hoc JBOD storage to an enterprise-grade shared storage platform spanning on-prem, colocation, and cloud, including architecture, vendor selection, and DR design. What You Will Bring - Bachelor's or Master's in Computer Science, Electrical Engineering, or a related field; 15+ years in SRE, infrastructure engineering, or production engineering. - 5+ years leading SRE or infrastructure engineering teams, including experience building or significantly rebuilding a function, not just managing a steady-state team. - Demonstrated track record of establishing SRE as a discipline in an organization that lacked it: defining SLOs, creating on-call frameworks, standing up observability, and driving cultural change with teams coming from a reactive ops background. - Deep Linux systems expertise: bare-metal operations, enterprise shared storage platforms (NAS/SAN, NFS/SMB at scale, snapshot and replication architectures), and hybrid-cloud storage integration. - Proven experience operating colocation and on-premises hardware at scale: server lifecycle, power and cooling awareness, rack-level networking. - Hands-on Infrastructure as Code fluency with Terraform and Ansible at production scale — module design, remote state, environment isolation, and change governance. - Kubernetes cluster operations: lifecycle management, workload reliability, storage, and RBAC at scale. - Full observability stack ownership (Prometheus, Grafana, Datadog and/or Splunk or equivalent) for SLO definition, alert design, and end-to-end signal quality. - Strong Python and/or Go scripting for production services and automation that safely touches real infrastructure. - Executive communication skills, translating infrastructure health and operational risk into clear narratives for senior leadership, including non-technical stakeholders. - Ability to operate in a high-ambiguity, low-process environment, building structure rather than inheriting it. Preferred Qualifications - Experience operating customer-facing infrastructure or platform services, with reliability expectations beyond internal tooling. - Knowledge of high-speed interconnect fabrics (InfiniBand, RoCE, or NVLink) — setup, troubleshooting, and performance tuning. - HPC job scheduler experience (Slurm, LSF, or equivalent) — setup, tuning, and integration with infrastructure automation. - Multi-cloud hybrid operations across AWS, Azure, and GCP alongside on-prem/colo, with unified observability and IaC. - FinOps expertise: cloud spend attribution, TCO modeling across cloud vs. on-prem vs. colo, and translating cost data into workload placement recommendations. - ITIL knowledge or an equivalent structured incident/problem/change management framework. - Published technical writing, conference talks, or open-source contributions in reliability, observability, or HPC infrastructure. Equal Opportunity Employment Policy d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day. d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.
Data Engineer
ABOUT CUSPAI CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us. THE ROLE As we grow, we are seeking a Data Engineer to play a crucial part in driving our research and development efforts forward. YOUR IMPACT As a Data Engineer you will be part of the new team building the infrastructure that underpins and acts as the critical bridge between raw chemical data and our machine learning models. Your main focus will be to build the pipeline infrastructure and tooling for data ingestion, moving towards self-serve setup for the scientific team members. You'll also be responsible for securing, collecting, cleaning, standardising, and tagging diverse chemical datasets to create high-quality training data for our ML researchers while working closely with our chemistry team to ensure scientific accuracy. WHAT YOU WILL DO Data Pipeline Development - Design and build robust data pipelines for materials science datasets, experimental results, and computational chemistry outputs. - Develop processes to integrate diverse data sources including materials databases, literature, patent filings, and laboratory instruments. - Create automated workflows for processing crystallographic data, molecular structures, and materials properties (you don’t need to have direct domain experience - we can help bring you up to speed!). - Build scalable systems to handle high-throughput computational chemistry calculations and experimental data. Data Quality & Standardisation - Partner closely with scientists to implement frameworks to automate quality checks for crystal structure data, chemical compositions, and experimental measurements. - Build monitoring systems to ensure data integrity across all pipelines. Collaboration & Integration - You will also be working hand in hand with ML researchers to understand data requirements for model training and inference. - Integrate with laboratory automation systems and computational chemistry software. - Support real-time data needs for AI-driven materials discovery experiments. MUST HAVE SKILLS AND QUALIFICATIONS - You are someone who gets excited about the opportunity to enable scientists to work on world changing challenges in this domain, with a personal interest in the potential applications of the technology that Cusp is building. - You’re a builder of tools and infrastructure who enjoys making life as easy as possible for the teams, providing self-serve, reliable and scalable ingestion pipelines. - You have at least 3+ years experience in data engineering roles, preferably in scientific or research environments - you would be joining as a data engineering subject matter expert who can not only work autonomously but also provide guidance on best practice. - High level of proficiency in Python and databases with experience in large-scale data processing - as part of our engineering team you’ll be programming regularly, not just scripting. - You’re an advanced user of workflow orchestration tools (e.g. Airflow, Prefect, Dagster, Flyte or similar). - Solid experience with containerisation (Docker, Kubernetes) and CI/CD practices. - You have direct experience handling large/complex datasets and are interested in working with scientific packages. - You’re a fast learner when it comes to new tools/systems. - You enjoy (and have experience in) designing systems that scale with growing data volumes and user demands. - Understanding and appreciation of DevOps practices is also important. BONUS POINTS (BUT NOT CRITICAL) - You’ve worked with data from scientific computing (simulations or experiments). - Knowledge of machine learning data requirements and MLOps practices, including pre-processing/processing as part of model training. - An academic background in Materials Science, Chemistry, Chemical Engineering, or related field. Even more bonus points if you have an understanding of crystallography, materials properties, and computational chemistry concepts! WHAT WE OFFER - A competitive salary: We value and reward impact and growth - Equity in CuspAI: You have a stake in the success of the company - Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays - ‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together - Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth - Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques - True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.
Application Scientist (AI Materials Science), Sing...
ABOUT CUSPAI CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us. THE ROLE Due to growth, we are seeking an experienced Application Scientist play a critical role in developing and applying the capabilities of our platform in partnership with our growing customer base. YOUR IMPACT In this role you will be working directly on a variety of customer and partner projects, supporting their teams to utilise our technology. Your work will be critical for solving complex problems for our customers and driving value for Cusp. As the primary liaison between external partners and internal teams, you will directly influence the success of our partnerships and the real-world application of our AI-driven materials discovery platform. Your main focus initially will be providing expert guidance, training, and technical support to external partners. You will also provide technical insights to enhance product development and application strategies. WHAT YOU WILL DO Technical Expertise & Guidance - Collaborate with sales and marketing teams to support customer engagement efforts and demonstrate the value of our technology. - Provide expert guidance to external partners on the application of our technology, addressing their technical questions and challenges. - Assist in troubleshooting technical issues and developing solutions that optimise product performance, supporting customer goals. - Act as the crucial bridge between external experimental teams (Chemists, Materials Scientists) and internal technical teams (Data Engineers, AI/ML Researchers). - Serve as CuspAI’s "eyes and ears" in the lab, providing regular technical reports and updates on experimental progress, status, and challenges. - Translate platform-driven recommendations into clear, executable experimental plans for our lab partners. - Communicate with lab teams regularly, including on-site visits to labs in different regions at the beginning of relationships and during intensive "sprint visits" to get labs online. Project Delivery & Reporting - Assist with project scoping and the creation of detailed technical proposals, helping to define project objectives. - Own the end to end delivery of specific projects, being a key point of contact along with the TPM and other technical team members. - Maintain accurate records of interactions with external partners, including training sessions, support requests, and feedback. - Prepare reports and presentations on the effectiveness of training and support initiatives. Training, Education, and Documentation - You may be required to develop and deliver training sessions, workshops, and presentations for external partners to enhance their understanding of our technology. If so, this would be done in collaboration with our existing team members. - Likewise, there may be times when you need to help create technical documentation, guides, and resources to facilitate the effective use of our platform. Product Improvement - Gather and analyse feedback from external partners regarding product performance and usability. - Work with TPMs, ML and platform engineers to relay insights and suggestions for enhancements based on partner experiences. - Stay informed about industry trends and advancements relevant to our technology, providing insights to improve applications and performance. MUST HAVE SKILLS AND QUALIFICATIONS: - Extensive, hands-on experimental lab experience in a relevant field such as Materials Science, Chemical Engineering, or Experimental Chemistry. - Exposure to AI/ML - ideally building or training models, but it's also fine if you have used them in any capacity. - Demonstrable automation mindset and experience optimizing or building interfaces for laboratory workflows and processes. - Solid scripting skills (Python) - you will need to handle data extraction, automate data translation between disparate laboratory and informatics systems, and to configure APIs for communication between laboratory and CuspAI’s systems. - Exceptional ability to communicate complex technical concepts effectively to both deeply scientific/technical audiences (AI researchers) and hands-on experimental teams (Chemists). - Proven ability to design and steer experimental campaigns based on defined objectives and data feedback. - A personal passion for the mission of CuspAI, particularly the potential of AI to unlock breakthroughs in materials science for sustainability, clean energy, or carbon capture. BONUS POINTS (BUT NOT CRITICAL): - Experience with high-throughput experiments (HTE), robotics, and commercial laboratory automation systems. - Professional-level coding skills, e.g. Python, Go. - Experience working with machine learning models or AI platforms, including an understanding of how data inputs affect model outputs and performance. - Knowledge of specific materials properties, crystallography, or computational chemistry concepts (e.g. DFT, MD simulations). - Proven ability to develop and deliver effective technical training sessions, presentations, and documentation to external partners. - Prior experience in a start-up or fast-growth technology company. ADDITIONAL CONSIDERATIONS This role will be based in Singapore, with the expectation of being in the office at least three days per week. Your working hours will need to have some overlap with our other teams in Europe, while also allowing you to work effectively with local partners. As part of your onboarding, you will be expected to spend at least a few weeks in our Cambridge/London office learning about our platform and getting to know us in person. Additionally, there may be regular travel required to Europe and other regional and global locations for collaboration and project work. WHAT WE OFFER - A competitive salary: We value and reward impact and growth - Equity in CuspAI: You have a stake in the success of the company - Time off to stay fresh: 28 days holiday (DE, NL, UK) or 21 days holiday (JP, SG, US), in addition to local public holidays - ‘Gold Standard’ parental leave: 26 weeks (primary caregiver) and 12 weeks (secondary caregiver) at full pay - we look after you and your family while we work on the most important materials discovery problems together - Professional development budget: We invest in your career development so you can stay up to date with the latest industry knowledge or add to your skills to increase impact and growth - Solve meaningful problems: See how your work has a direct impact on advancing materials science and solving sustainability and climate-related problems through the creation and application of bleeding-edge SOTA technology and revolutionary techniques - True interdisciplinary teamwork: Be part of a deeply collaborative environment bridging AI research, computational chemistry, and experimental science - work with world-class researchers and engineers who enjoy sharing knowledge and supporting each other Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know if you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.
Staff Technical Program Manager, Managed Intellige...
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role: Crusoe is the world's first vertically integrated, sustainable AI cloud. We build and operate GPU infrastructure powered by clean energy, from data center design through IaaS products to managed inference at scale, enabling AI-native companies to run demanding workloads without compromising on sustainability or reliability. Crusoe Cloud is 1,400 people and growing, and the TPM frameworks are still being built -- which means there is a genuine opportunity to shape how the function operates rather than inherit how it already works. The Managed Inference platform is where customers run production LLM workloads without managing low-level infrastructure, and it is one of Crusoe's fastest-growing product areas. The Staff TPM for Managed Intelligence connects model engineering, IaaS, product, and data center operations to deliver a reliable, scalable inference platform. You will own end-to-end program delivery across multi-quarter roadmaps, model onboarding, inference optimization, and production readiness for new model versions. Deep familiarity with the model layer -- including how LLMs are served, optimized, and evaluated in production -- is essential to being effective in this role. What You'll Be Working On: - End-to-end program delivery: Own multi-quarter release planning, dependency governance, and executive communication across the Managed Inference platform. - Complex, high-risk program management: Drive model version rollouts, inference optimization campaigns, SLA readiness for new GPU hardware, and multi-tenant capacity planning from kickoff through delivery. - Cross-functional alignment: Coordinate across Model Engineering, IaaS, Cloud Foundations, Data Center Operations, and external model providers to keep programs on track and unblocked. - Proactive risk identification: Surface risks across model serving, reliability, capacity constraints, and vendor timelines before they become program-level problems. - Execution frameworks and dashboards: Build lightweight, scalable TPM frameworks suited to Crusoe's pace; maintain real-time execution dashboards and deliver crisp, data-driven executive updates. - Phase 0 planning for model onboarding: Own pre-launch planning for model onboarding on new GPU generations, including firmware and driver readiness, CUDA and ROCm stack validation, and commissioning criteria for inference workloads. - Stakeholder leadership: Drive alignment and push back effectively across engineering, product, and operations leadership -- including highly technical stakeholders who have not previously worked with a TPM. What You'll Bring to the Team: - 7+ years of experience as a Technical Program Manager in fast-paced technical environments, with a track record of owning complex programs end-to-end across engineering and product organizations. - LLM inference and model serving knowledge: Working familiarity with batching strategies, quantization approaches, and the tradeoffs that govern latency, throughput, and cost at production scale. - Multi-tenant systems experience: Familiarity with isolation, quota management, and SLA enforcement across concurrent workloads. - Fine-tuning and alignment awareness: Sufficient familiarity with fine-tuning and alignment workflows to govern program timelines, identify technical risks, and coordinate across the teams that own them. - Low-structure execution: Proven ability to build execution models in environments where the process did not yet exist, and make them stick with teams that didn't ask for them. - Executive communication: Exceptional written and verbal communication for delivering clear, data-driven, decision-oriented updates to executive stakeholders. - AI tool integration: Active, daily use of AI tools to improve program execution, risk detection, and communication -- not just personal productivity. - Cross-functional influence: Proven ability to drive alignment across engineering, product, and infrastructure leadership without direct authority, including with highly technical stakeholders. Bonus Points: - 1+ years of experience working with teams building platforms or services for AI inference and/or training. - Direct experience governing model onboarding programs across GPU generations, including firmware, driver, and stack validation. - Experience coaching or mentoring junior TPMs in a high-growth technical environment. - Exposure to multi-site or globally distributed engineering teams. - Background at a Series D to Series F company or a high-performing team within a hyperscaler focused on AI infrastructure. Benefits: - Competitive compensation and equity packages - Restricted Stock Units - Paid time off, paid holidays & leave of absence programs - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off - Global travel insurance & emergency assistance - Daily meals allowance - Additional perks & programs specific to location Compensation Range Compensation will be paid in the range of up to $200,000 - $240,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
Staff Software Engineer, Storage
Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster. We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI. We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services. If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe. About This Role The Cloud Storage team at Crusoe is seeking a Staff Software Engineer to serve as a primary architect and visionary for our storage strategy. While a Staff Engineer leads features, a Senior Staff Engineer defines the multi-year technical roadmap that underpins our AI-scale infrastructure. You will be a multiplier, responsible for the architectural strategy, integrity and global scalability of our bespoke storage services. You will work at the physics of the stack, bridging the gap between high-performance NVMe hardware and globally distributed, S3-competitive object stores. What You’ll Be Working On - Architectural Vision & Strategy: Define and drive the long-term technical strategy for Crusoe’s storage engine. Identify industry trends (e.g., CXL, NVMe-oF) and integrate them into a cohesive roadmap. - System Programming Expertise: Leverage proven experience in system programming with languages such as C, C++, Go, and/or Rust to build the foundations of our V2 storage re-architecture. - Storage Protocols: Architect and implement solutions utilizing industry-standard storage protocols such as NFS, SMB, iSCSI, and NVMe/TCP. - Open Source Stewardship: Drive and maintain a track record of contributions to the open-source community (e.g., Ceph, GlusterFS, Lustre, Spectrum Scale, OpenEBS). - Technical Authority: Serve as the final arbiter for critical architecture decisions across the Foundations organization. Lead complex design reviews that intersect storage, networking, and virtualization. - Deep Performance Engineering: Lead "tiger teams" to solve the most ambiguous and difficult bottlenecks in the stack—from kernel-level IO context switching to global tail-latency in distributed clusters. - Strategic Collaboration: Work closely with Executive Leadership and Product to align technical capabilities with business milestones, such as our imminent path to IPO. What You’ll Bring to the Team - Cloud Storage Expertise: 12+ years of experience building and operating large-scale, complex distributed cloud computing infrastructure products. - Troubleshooting & Tuning: Strong troubleshooting and performance tuning skills; ability to profile and optimize the entire IO path. - High-Drive Mindset: Self-motivation to thrive in a fast-paced environment with a high degree of ownership and minimal supervision. - Masters of Consistency & Durability: Deep theoretical and practical knowledge of distributed state and data protection at petabyte scale. - Software Engineering Fundamentals: Mastery of professional software engineering practices for the full SDLC, including coding standards, build processes, and testing. - Communication & Collaboration: Ability to champion and lead initiatives across the engineering organization, such as tech talks and technical reading groups. Bonus Points - Public Cloud & AI/ML: Expertise in one or more Public Cloud offerings (AWS, GCP, Azure, OCI) and familiarity with AI/ML frameworks (PyTorch, Tensorflow, JAX) and MLOps. - High-Throughput I/O: Experience with cutting-edge I/O architectures like DAOS or SPDK. - Networking Foundations: Background in RDMA and high-performance networking, including SmartNICs and RoCEv2. - Distributed Systems Mastery: Experience with highly available and scalable systems such as Cassandra, MongoDB, Redis, or Kafka. - Theoretical Depth: Strong knowledge of distributed systems fundamentals including CAP Theorem, Paxos/RAFT, consistent hashing, and sharding strategies. - Education: Advanced degree (Master's or PhD) in Computer Science, Engineering, or a related field. Benefits: - Competitive compensation - Restricted Stock Units - Paid time off & paid holidays - Comprehensive health, dental & vision insurance - Employer contributions to HSA account - Paid parental leave - Paid life insurance, short-term and long-term disability - Professional development & tuition reimbursement - Mental health & wellness support - Commuter benefits (parking & transit) - Cell phone stipend - 401(k) Retirement plan with company match up to 4% of salary - Volunteer time off Compensation Range Compensation will be paid in the range of up to $215,000 - $260,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data. Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.
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