Together AI

About the role Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Responsibilities - Build and own bespoke ABM programs for our top accounts, partnering with Sales on account tiering, buying group mapping, and the plays that drive marketing activation and air cover. - Design and run integrated campaigns across paid media, email, content syndication, webinars, gifting, and meeting-maker programs, connecting them into cohesive journeys rather than standalone tactics. - Partner with Field Marketing and Events on pre-event account targeting and warm-up, digital amplification, and post-event retargeting. - Develop campaign architecture, messaging, and creative across the customer journey in partnership with Product Marketing, Brand, Design, and Content, keeping positioning consistent across every campaign touchpoint. - Run continuous testing and experimentation across channels — from ad creative and landing pages to targeting and channel mix — to improve conversion and pause what isn't working. - Work with RevOps as the business owner of our demand gen and ABM stack, influencing what to evaluate, buy, or build in-house with AI tooling. - Own account penetration and pipeline contribution against new logo goals, managing campaign performance and building the reporting framework that defines what success looks like. Requirements - 6+ years in B2B demand generation, campaigns, or ABM, preferably at SaaS or AI-native/digital-first companies, with experience marketing to technical decision makers and practitioners across engineering, IT, or cybersecurity. - Proven track record building and scaling integrated campaigns across digital, events, content, and account-based channels, including where process didn't exist yet. - Deep ABM expertise across account tiering, buying group mapping, intent data, orchestration, and measurement. - Experience working with digital agencies across paid social and search. - Marketing automation and campaign operations fluency (Marketo, HubSpot, or similar) with an understanding of lead lifecycle management. - Data-driven, comfortable working in reporting tools like Hex or Tableau to interpret campaign performance and communicate it clearly to stakeholders. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, reinforcement learning to create specialized models, and pre-training for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves over 400 trillion tokens a month Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $ 190K - $225K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy .

About the role As a Technical Support Engineer at a pioneering AI company, you'll be the first line of defense to support customers as they build out training, fine tuning, and inference solutions with Together AI. You'll dive deep into complex technical challenges, providing swift and effective solutions while serving as a product expert. As a part of the Customer Experience organization, you will collaborate closely with product and sales, driving continuous improvement of our offerings. This is an exciting opportunity for a deeply technical professional passionate about AI and customer success to make a significant impact in a fast-paced, innovative environment. Responsibilities - Triage and respond to inbound support tickets across self-serve and enterprise customers using a support/CRM platform; identify patterns in ticket clusters (e.g., a wave of the same error code), surface them to engineering with context and affected case lists, and follow through to resolution. - Draft clear, accurate status updates and maintenance notifications for customers during planned maintenance windows or incidents; communicate expected impact without exposing internal platform details. - Collaborate seamlessly across Engineering, Research, and Product teams to address customer concerns; collaborate with senior leaders both internally and externally to ensure the highest levels of customer satisfaction. - Answer customer questions about the platform's API, model/fine-tuning workflows, model availability, and deployment/endpoint configuration; reproduce reported errors to confirm expected vs. broken behavior and provide actionable next steps. - Provision and configure SSO connections for enterprise customers (Google Workspace, Okta, Azure AD, etc.); guide customers through IdP-side setup steps; diagnose login failures by cross-referencing the platform's identity provider configuration against the customer's; escalate confirmed platform-side gaps. - Triage customer billing questions using billing/subscription tooling (e.g., Stripe, Metronome, or equivalent); process or coordinate refunds for prepaid credits and disputed charges; investigate negative-balance and credit-limit enforcement issues; escalate edge cases to the billing/finance team with full context. - Resolve API key creation failures, org linkage issues, and project/key limit requests; coordinate user access changes (adding/removing org members, SSO org ownership transfers); investigate tenant isolation issues. Requirements - 2+ years of experience in a customer-facing technical role - Comfortable reading and writing curl/HTTP requests, interpreting JSON error responses, and understanding concepts like bearer tokens, rate limits, and API key scoping; no deep software engineering background required, but must be able to follow and reproduce API-level issues. - Familiarity with how SaaS billing works (invoices, prepaid credits, refunds); comfortable navigating admin dashboards and understanding what a payment state means. - Working knowledge of SAML and OIDC concepts (ACS URL, audience URI, attribute mapping, IdP vs. SP); enough to walk a customer's IT admin through a configuration and recognize whether an error is on the customer side or platform side. - Familiarity with infrastructure services (e.g., Kubernetes, SLURM), infrastructure as code solutions (e.g., Ansible) high-performance network fabrics, NFS-based storage management, container infrastructure, and scripting and programming languages. - Excellent communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders. - Prior experience with a customer support platform (Zendesk, Intercom, Pylon, Freshdesk, or similar); comfortable managing a queue, updating ticket state, and writing internal notes. - Familiarity with how language model APIs work (tokens, context windows, serverless vs. dedicated inference) - Strong sense of ownership and willingness to learn new skills to ensure both team and customer success. - Ability to operate in dynamic environments, adept at managing multiple projects, and comfortable with frequent context switching and prioritization. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our Privacy Policy at https://www.together.ai/privacy

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructure at massive scale, and help define how self-improving AI agents operate real-world AI infrastructure. Responsibilities - Design and build production AI agent systems that diagnose, investigate, and remediate infrastructure issues across one of the world’s largest GPU fleets. - Build the distributed services, orchestration framework, knowledge graph, and retrieval systems that power infrastructure agents. - Develop fleet intelligence systems that combine telemetry, infrastructure state, operational knowledge, and historical incidents to help agents make better decisions. - Integrate with observability, incident management, ticketing, fleet inventory, source control, chat, and internal infrastructure systems through well-designed APIs. - Own services end to end, including architecture, implementation, testing, deployment, observability, and production operations. - Improve agent performance through evaluations, retrieval improvements, better tools, and production feedback loops. - Turn what agents learn in production into reliable, reviewed software and automation. Requirements - 5+ years of experience building production backend systems, distributed systems, or infrastructure platforms. - Strong systems design skills and experience owning significant systems from design through production. - Depth in at least one of the following: - AI agent systems, orchestration, tool use, evaluation, or grounding - Knowledge graphs or graph data modeling - Search, retrieval, ranking, RAG, or semantic search systems - Strong backend engineering experience, including API design, service boundaries, data modeling, and integrations across complex systems. - Experience with Kubernetes, GitOps such as ArgoCD, infrastructure-as-code, and cloud platforms. - Comfortable working across languages such as Go, TypeScript, Python, or Rust. Experience in the following is a plus: - GPU infrastructure, datacenters, bare-metal systems, hardware failure modes, BMC/IPMI, or cluster schedulers - Graph databases - Event-driven systems and messaging platforms such as NATS or Kafka - Observability platforms such as Prometheus and Grafana - Building evaluation frameworks or improving the quality and reliability of LLM-powered systems About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $250,000 - $300,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy .

About the Role In this role, you will operate, scale, and optimize multi-petabyte storage systems purpose-built for the world’s largest AI training and inference workloads. You’ll manage and scale high-performance parallel filesystems and object stores, evaluate and integrate cutting-edge technologies such as Vast, Weka, Ceph, and Lustre, and solve the complex engineering challenges of operating at extreme throughput, low-latency data paths, and massive cluster-scale storage operations. You will also build Kubernetes-native storage operators and self-service platforms that provide automated provisioning, strict multi-tenancy, performance isolation, and quota enforcement at cluster scale. Day-to-day, you’ll optimize end-to-end data paths for 10-50 GB/s per node, design multi-tier caching architectures, implement intelligent prefetching and model-weight distribution, and tune parallel filesystems for AI workloads. Responsibilities - Architect and implement the technical strategy and storage roadmap for Together AI, driving high-performance architectural decisions as we scale our GPU fleet. - Engineer and scale multi-petabyte AI/ML storage systems by integrating Vast, Weka, and Ceph while executing deep cost optimization through automated tiering and lifecycle policies. - Develop intelligent caching and tiered storage architectures to achieve extreme IOPS and cluster-wide throughput at GPU scale for training and inference workloads. - Tune storage isolation at the L2/L3 network layers to ensure secure, production-grade multi-tenancy for storage clients. - Code Kubernetes storage operators and controllers to enable automated provisioning, self-service abstractions, and quota enforcement. - Engineer end-to-end data paths to achieve 10+ GB/s per GPU node; architect multi-tier caching for model weights and datasets; tune parallel filesystems using advanced profiling; and scale storage infrastructure across thousands of nodes. - Optimize end-to-end data paths through advanced benchmarking and profiling, contributing high-impact code to open-source storage projects and internal tooling. Requirements - 8+ years in storage engineering, managing distributed storage at multi-petabyte scale - Proven track record deploying and operating high-performance storage for GPU/HPC clusters - Deep Kubernetes and cloud-native storage experience in production environments - Strong coding skills in Go and Python with demonstrated ability to build production-grade systems and tooling - BS/MS in Computer Science, Engineering, or equivalent practical experience - History of technical leadership: designing systems that significantly improved performance, reliability (99.999%+ uptime), or cost efficiency - Distributed Storage Systems: Deep expertise in either of Ceph, WekaFS, Lustre, Vast, GPFS, or similar parallel filesystems at multi-petabyte scale - Object Storage: Production experience with S3, MinIO, Ceph, or R2 including performance optimization and cost management - Kubernetes Storage: CSI drivers, StatefulSets, PersistentVolumes, storage operators, and custom controllers - Storage optimization for GPU workloads, RDMA/InfiniBand networking, parallel filesystem optimization (TB/s aggregate cluster throughput - line saturation) - Programming: Go and Python for automation, operators, and tooling - Infrastructure as Code: Terraform, Ansible, Helm, GitOps (ArgoCD) - Linux Storage Stack: Advanced knowledge of filesystems (ext4, xfs), LVM, NVMe optimization, RAID configurations - Observability: Prometheus, Grafana, Thanos architecture and operations Nice to Have Skills - GPU Direct Storage (GDS), NVMe-oF, storage networking, RDMA implementations - ML/AI storage patterns (model weights, checkpointing, dataset caching) - Storage benchmarking and profiling tools (fio, iperf3, iostat, blktrace) About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy

About the role We're hiring a Senior ABM & Campaign Manager to join our Demand Generation team. You'll own our account-based programs and the integrated campaigns that reach AI-native and digital-native companies running inference at scale. That means designing and executing campaigns from first touch to pipeline across content, digital, and the account-based experience, then shaping how we measure what works as we grow. Responsibilities - Build and own bespoke ABM programs for our top accounts, partnering with Sales on account tiering, buying group mapping, and the plays that drive marketing activation and air cover. - Design and run integrated campaigns across paid media, email, content syndication, webinars, gifting, and meeting-maker programs, connecting them into cohesive journeys rather than standalone tactics. - Partner with Field Marketing and Events on pre-event account targeting and warm-up, digital amplification, and post-event retargeting. - Develop campaign architecture, messaging, and creative across the customer journey in partnership with Product Marketing, Brand, Design, and Content, keeping positioning consistent across every campaign touchpoint. - Run continuous testing and experimentation across channels — from ad creative and landing pages to targeting and channel mix — to improve conversion and pause what isn't working. - Work with RevOps as the business owner of our demand gen and ABM stack, influencing what to evaluate, buy, or build in-house with AI tooling. - Own account penetration and pipeline contribution against new logo goals, managing campaign performance and building the reporting framework that defines what success looks like. Requirements - 6+ years in B2B demand generation, campaigns, or ABM, preferably at SaaS or AI-native/digital-first companies, with experience marketing to technical decision makers and practitioners across engineering, IT, or cybersecurity. - Proven track record building and scaling integrated campaigns across digital, events, content, and account-based channels, including where process didn't exist yet. - Deep ABM expertise across account tiering, buying group mapping, intent data, orchestration, and measurement. - Experience working with digital agencies across paid social and search. - Marketing automation and campaign operations fluency (Marketo, HubSpot, or similar) with an understanding of lead lifecycle management. - Data-driven, comfortable working in reporting tools like Hex or Tableau to interpret campaign performance and communicate it clearly to stakeholders. About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190K - $225K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy .

About the role As a Forward Deployed Engineer (FDE) focused on Inference & Post-Training, you will be a hands-on technical partner to our most strategic customers — production AI teams looking to leverage high quality models and do inference at scale. For us, FDE is not a replacement for a Solutions Architect; you will partner with our SAs as a deep-domain specialist in inference optimization, fine-tuning pipelines, and production deployment. As key contributors to both the CX, Engineering, and Sales organizations, FDEs add tremendous value by ensuring we can meet the requirements of our most complex POCs, facilitate successful platform adoption, and guide tailored optimization efforts — directly impacting customer success, company growth, and the hardening of our core platform. Responsibilities - Inference Engine Optimization: Select, configure, and optimize inference engine based on hardware, model architecture, and workload profile - Configuration & Performance Tuning: Develop configuration updates to win critical POCs, benchmarks, and optimize customer deployments; tune KV cache, apply speculative decoding, determine optimal tensor parallelism, and determine quantization strategy to hit throughput and latency targets. - Post-Training & Fine-Tuning: Drive hands-on RL training runs and optimize system design; guide customers through LoRA, SFT, DPO, RLHF, and GRPO pipelines from experimentation through production. - Strategic Customer Alignment: Act as the primary technical point of contact for aligned strategic accounts — monitoring and optimizing endpoint configurations, helping customers get the most out of the platform, and collaborating to ensure we hit critical milestones. - Opinionated Onboarding: Establish direct alignment with strategic customers at onboarding; ensure the right inference and post-training configurations are in place from day one to improve time-to-value. - Product Feedback Loop: Directly influence our software and model roadmap by surfacing insights from the field. Contribute back to the product where needed to support customer requirements or drive a better experience. Drive early feature and research adoption with strategic logos. Qualifications - Experience: 5+ years in a technical role, with a strong focus on inference systems, open-source LLM deployment, or post-training workflows. - Inference Engine Depth: Expert-level, hands-on experience with inference engines (e.g., vLLM, TensorRT-LLM, SGLang); ability to diagnose and resolve performance issues at the engine level. - Inference Optimization: Deep knowledge of KV cache tuning, speculative decoding, tensor parallelism, pipeline parallelism, and quantization techniques - Post-Training Knowledge: Hands-on experience with fine-tuning and post-training pipelines, including LoRA, SFT, DPO, RLHF, and GRPO; ability to advise on system design - Model Landscape Awareness: Broad knowledge of state-of-the-art open-source models and strong judgment on model selection for specific customer use cases, hardware profiles, and performance targets. - Coding Proficiency: Strong Python skills; comfortable working in production environments About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competitive compensation, startup equity, health insurance, and other benefits, as well as flexibility in terms of remote work. The US base salary range for this full-time position is: $270,000 - $300,000 OTE + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our Privacy Policy at https://www.together.ai/privacy

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructure at massive scale, and help define how self-improving AI agents operate real-world AI infrastructure. Hybrid in Amsterdam Responsibilities - Design and build production AI agent systems that diagnose, investigate, and remediate infrastructure issues across one of the world’s largest GPU fleets. - Build the distributed services, orchestration framework, knowledge graph, and retrieval systems that power infrastructure agents. - Develop fleet intelligence systems that combine telemetry, infrastructure state, operational knowledge, and historical incidents to help agents make better decisions. - Integrate with observability, incident management, ticketing, fleet inventory, source control, chat, and internal infrastructure systems through well-designed APIs. - Own services end to end, including architecture, implementation, testing, deployment, observability, and production operations. - Improve agent performance through evaluations, retrieval improvements, better tools, and production feedback loops. - Turn what agents learn in production into reliable, reviewed software and automation. Requirements - 5+ years of experience building production backend systems, distributed systems, or infrastructure platforms. - Strong systems design skills and experience owning significant systems from design through production. - Depth in at least one of the following: - AI agent systems, orchestration, tool use, evaluation, or grounding - Knowledge graphs or graph data modeling - Search, retrieval, ranking, RAG, or semantic search systems - Strong backend engineering experience, including API design, service boundaries, data modeling, and integrations across complex systems. - Experience with Kubernetes, GitOps such as ArgoCD, infrastructure-as-code, and cloud platforms. - Comfortable working across languages such as Go, TypeScript, Python, or Rust. Experience in the following is a plus: - GPU infrastructure, datacenters, bare-metal systems, hardware failure modes, BMC/IPMI, or cluster schedulers - Graph databases - Event-driven systems and messaging platforms such as NATS or Kafka - Observability platforms such as Prometheus and Grafana - Building evaluation frameworks or improving the quality and reliability of LLM-powered systems About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

About the Role As a Sales Development Engineer Representative at Together.ai, your territory is the world. You will have the opportunity to be at the cutting edge of one of the most important technological shifts of our time, speaking daily with founders, data scientists, researchers, and CTOs to help them build successful AI-driven businesses. Your primary focus will be to surface, qualify, and convert opportunities for potential prospects or users on the Together platform, focusing on both GPU sales & API platform sales. The ideal candidate will have a passion for technology, entrepreneurship & AI, and thrive in a fast paced environment. Requirements - 1-2 years of technical experience or education and interest in customer facing roles - Desire to work with highly technical teams and products - An excellent communicator with both clients and internal teams - Adaptability, coachability, high drive and sense of urgency - enjoys working within a fast-paced environment wearing multiple hats - Enjoys experimenting with the sales pitch/process to achieve company goals - Experience and success with cold & warm calling/prospecting, making high volumes of calls & emails daily Nice to Have - 2 years of experience in sales, with a track record of exceeding targets - Baseline understanding of compute hardware products Responsibilities - Convert inbound interest or source outbound interest and convert into commercial contracts alongside Account Executives - Convert users of the Together platform to broader commercial opportunities alongside Account Executives - Collaborate on product roadmaps & features by bringing the voice of the customer into Together - Meticulously prospect and manage a pipeline of new business opportunities in CRM (Pipedrive, Salesforce, etc) - Generate sales interest via multi-channels About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $90K-150K + commission + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructure at massive scale, and help define how self-improving AI agents operate real-world AI infrastructure. Remote based in the UK Responsibilities - Design and build production AI agent systems that diagnose, investigate, and remediate infrastructure issues across one of the world’s largest GPU fleets. - Build the distributed services, orchestration framework, knowledge graph, and retrieval systems that power infrastructure agents. - Develop fleet intelligence systems that combine telemetry, infrastructure state, operational knowledge, and historical incidents to help agents make better decisions. - Integrate with observability, incident management, ticketing, fleet inventory, source control, chat, and internal infrastructure systems through well-designed APIs. - Own services end to end, including architecture, implementation, testing, deployment, observability, and production operations. - Improve agent performance through evaluations, retrieval improvements, better tools, and production feedback loops. - Turn what agents learn in production into reliable, reviewed software and automation. Requirements - 5+ years of experience building production backend systems, distributed systems, or infrastructure platforms. - Strong systems design skills and experience owning significant systems from design through production. - Depth in at least one of the following: - AI agent systems, orchestration, tool use, evaluation, or grounding - Knowledge graphs or graph data modeling - Search, retrieval, ranking, RAG, or semantic search systems - Strong backend engineering experience, including API design, service boundaries, data modeling, and integrations across complex systems. - Experience with Kubernetes, GitOps such as ArgoCD, infrastructure-as-code, and cloud platforms. - Comfortable working across languages such as Go, TypeScript, Python, or Rust. Experience in the following is a plus: - GPU infrastructure, datacenters, bare-metal systems, hardware failure modes, BMC/IPMI, or cluster schedulers - Graph databases - Event-driven systems and messaging platforms such as NATS or Kafka - Observability platforms such as Prometheus and Grafana - Building evaluation frameworks or improving the quality and reliability of LLM-powered systems About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy

About the Role We are seeking a highly analytical and detail-oriented Data Analytics Engineer to join our data team. This role will report into the Revenue Operations team. The ideal candidate will help build and maintain the data infrastructure and reporting used across go-to-market, finance, and product teams, working closely with analytics colleagues across both the GTM and core data teams to deliver reliable, well-documented data products. Responsibilities - Develop and maintain dashboards and reports primarily supporting GTM stakeholders, with additional use by Finance, Product, and other cross-functional teams; assist with deep-dive analyses on business performance and trends. - Pull and analyze data from source systems (Salesforce, Amplitude, production systems, billing) to support reporting and ad hoc requests. - Use SQL to extract, clean, and analyze data, with attention to correctness and efficiency. - Build foundational SQL and business knowledge and quickly grow into contributing to dbt models within Snowflake, following established dimensional modeling standards. - Partner with GTM, Finance, and Product stakeholders to understand data needs and keep reporting and definitions consistent. Requirements - Bachelor's degree in Business Analytics, Data Science, Statistics, Computer Science, or a related quantitative field. - 1-3 years of experience in a Data Analyst, BI, or Analytics Engineering role. - Strong SQL skills required, with the ability to write complex, multi-step queries involving joins and aggregations; experience with dbt and/or Python is a strong plus. - Familiarity with a cloud data warehouse (Snowflake preferred) and BI tools (Hex, Metabase). - Strong attention to detail and ability to manage multiple priorities in a fast-paced environment. - Excellent communication skills, with the ability to explain data findings to non-technical stakeholders. About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $ 120K - $150K + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. Please see our privacy policy at https://www.together.ai/privacy .