Netflix

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. The Demand Science team within Ads Data Science & Engineering plays a crucial role in Netflix Ads growth by equipping the business to efficiently attract, activate, and scale advertiser demand. As the dedicated ML lead for Sales productivity and automation within the Sales pod, you would partner closely with Product Managers, Engineers, and Sales stakeholders to identify where AI can drive the most impact — and then build it. We're looking for someone who can identify the highest-leverage opportunities, propose solutions, and drive them end-to-end to transform how Netflix's ad sales business operates, using data science, AI, and machine learning to help sellers work smarter, close more deals, and scale Ads revenue without scaling headcount at the same pace. The Scope As the ML lead for Sales productivity and automation, you'll own the technical vision and execution across areas such as: - Workflow Automation : In partnership with Product, identify and automate high-friction points in the Sales workflow to reduce delays, eliminate manual work, and improve accuracy — so sellers spend less time on process and more time on selling. - AI-Augmented Selling : Design and deploy AI agents and assistants that make selling faster and more effective — automating where possible and helping sellers prepare for client conversations, respond to RFPs, and close higher-value deals more quickly. What You’ll Do - Define the AI/ML investment roadmap for the Sales pod in close partnership with product and engineering, identifying where data science can drive the most meaningful improvements in Sales productivity and revenue outcomes. - Design, build, and deploy production ML models, AI agents, and automation systems end-to-end. - Partner with Analytics Engineers to build the metrics, measurement pipelines, and reporting that guide investment decisions and track product performance. - Iterate on launched products based on performance data and seller feedback, with a clear eye on measurable business impact. - Serve as a senior technical voice in cross-functional discussions, communicating clearly with both technical and non-technical stakeholders. Who You Are - Advanced degree (PhD or Master's) in Computer Science, Statistics, Mathematics, or a related quantitative field. - Track record of independently scoping and leading end-to-end ML projects in production environments — not just executing on defined projects, but identifying the right problems to solve and driving them from idea to measurable impact. - Strong strategic acumen: the ability to understand business objectives deeply and translate them into a prioritized technical roadmap. - Comfort with ambiguity and a proactive, curious approach to problem-solving — you can operate effectively in a space where the path isn't always laid out for you. - Excellent communication skills with both technical and non-technical audiences, paired with the curiosity and user empathy to understand Sales pain points and needs. - Proficiency in Python and SQL for building ML pipelines and models. - Experience with LLMs, AI, or agentic systems is a bonus, but not required, given how new these fields are - we think candidates with strong ML product-building experience willing to learn into AI can also be highly successful in this role. - The Netflix Culture Memo resonates with you. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. Netflix is the world's leading streaming entertainment service with 300M+ paid memberships in over 190 countries enjoying TV series, documentaries and feature films across a wide variety of genres and languages. Machine Learning drives innovation across all product functions and decision support needs. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. We are seeking an ambitious software engineer to join the Model Development and Management team, that is building the user interface layer for Netflix’s AI Platform in order to accelerate the core loop of model creation, evaluation, experimentation, and deployment. In this role, you'll help shape the future of ML infrastructure at Netflix, with opportunities to contribute to open-source projects and you’ll develop expertise across the full ML lifecycle while working with cutting-edge technologies. AI Platform and Model Development and Management team are working with various teams at Netflix. You’ll gather requirements, design, and implement products that help accelerate model development for different ML use cases. You’ll have the opportunity to work alongside our applied researchers and data scientists on the cutting edge of machine learning. You will have a strong customer focus and consistently engage with our ML community to source feedback, identify pain points, and opportunities to evolve our platform. To be successful in this role, you must have a strong software engineering background, a keen sense of software design, have proven experience with distributed applications and ML systems, be a good communicator, and work well in large cross-functional teams. What we are looking for: - Experience developing platform solutions - SDKs, developer frameworks, or internal tooling used by ML Researchers, ML Engineers, and Data Scientists, emphasizing a user-first approach and demonstrating strong user empathy. - Excellent software design and development skills in Python along with one of Scala, Java, C++. - Experience working on or alongside modern, large-scale ML services. You understand the full lifecycle from data and features to training, experiment tracking, and production deployment, and can build tooling that makes that lifecycle faster and more reliable. - Familiarity with ML workflow orchestration, experiment tracking, or feature/data infrastructure — ideally with tools like Metaflow, Airflow, Kubeflow, MLflow, or similar. - Broad understanding of core machine learning concepts and their application in large-scale, real-world machine-learning systems. - 5+ years of full time software engineering or machine learning experience with a bachelor’s and master’s degree; or PhD degree. Preferred, but not required additional areas of experience: - Experience building machine learning models or LLMs - Experience designing or building agentic systems. - Experience working with public clouds, especially AWS. - Significant contributions to open source projects. More information To learn more about the work we do to check if it aligns with your interests, check the following articles: - Supporting Diverse ML Systems at Netflix - Metaflow Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. We launched a new ad-supported tier in November 2022 and are building an in-house world-class ad tech ecosystem to offer our members more choices in consuming their content. Our new tier allows us to attract new members at a lower price point while also creating a compelling path for advertisers to reach deeply engaged audiences. Our Team The Decisioning & Optimization engineering team owns the systems that determine which ad wins every impression, at what price, and how campaign budgets deliver across all inventory surfaces. Our work spans three platform areas: - ML infrastructure for model serving : real-time inference at 1M+ QPS, multi-model parallel evaluation, feature hydration, model lifecycle from canary deployment through production monitoring - Auction, ranking, and scoring : multi-stage candidate selection, scoring, bid valuation, dynamic pricing, and podding - Budget, pacing, and bidding : control systems for delivery optimization, budget planning, and bid computation We are scaling from a handful of production models to 10+ while maintaining sub-20ms P99 inference budgets. We are looking for an ML engineer who can build and operate the serving infrastructure these models run on, and who understands the ads decisioning context well enough to make the right engineering tradeoffs. What You'll Do - Build and operate end-to-end ML model serving infrastructure for real-time ad decisioning: model publishing, packaging, validation, deployment into the serving stack with zero-downtime hot-swap - Scale the inference path to support dozens of concurrent models on every ad request at 1M+ QPS with strict latency budgets, including batching strategies, CPU/GPU allocation, model versioning, and fallback tiers - Design and optimize the feature serving path: feature hydration from Chronon, Signal Service, and real-time streams with sub-10ms P99 fetch latency and online/offline consistency - Productionize scoring and ranking models for multi-stage ad selection (retrieval, early ranking, full scoring) and integrate model outputs into auction - Build model performance monitoring in production: inference latency, prediction distribution shifts, feature drift detection, score calibration, and regression detection before revenue impact - Partner closely with Data Science & Platform teams - Build simulation infrastructure to replay production traffic against candidate models offline, enabling validation of marketplace changes before live rollout - Drive operational excellence for ML systems: reliability, observability, capacity planning, incident response, and scaling for live events with 35M+ concurrent viewers Skills & Experience We're Seeking - 7+ years of software engineering experience; 3+ years focused on ML infrastructure, model serving, or ML platform work in an ads or real-time decisioning context - Built and operated real-time model serving systems at high QPS with sub-20ms latency: online inference, feature stores, model registries, model hot-swap, canary and shadow rollout - Proficiency in Java, Python, or Scala with a solid understanding of multi-threading, memory management, and performance optimization for latency-critical paths - Hands-on with ML serving frameworks: serialization, runtime optimization, and deployment constraints - Experience with feature engineering pipelines for real-time systems: online/offline consistency, hydration strategies, caching, and freshness tradeoffs - Strong understanding of model monitoring in production: drift detection, prediction distribution analysis, calibration, and latency profiling - Comfortable working at the boundary between ML research and production engineering: can take a model artifact and turn it into a production-ready service that meets SLA - Demonstrated ability to operate in an environment that requires both big-tech scale and startup speed Nice to Haves - Ads domain experience: ranking models, bid scoring, reserve pricing, yield optimization, dynamic allocation across guaranteed and non-guaranteed inventory - Experience with auction mechanics: multi-stage ranking, bid shading, bid prediction, marketplace competition dynamics - Built or improved budget pacing and delivery control systems - Built simulation or counterfactual testing platforms for marketplace or auction systems - Experience with A/B testing infrastructure for model rollouts: online experiments, holdout groups, interference-aware evaluation in marketplace settings - Familiar with CTV constraints: server-side ad insertion, live event ad serving at scale, burst traffic patterns - JVM ecosystem Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. In 2022 we launched a new lower-priced, ad-supported tier, and we are building an in-house, world-class ad-tech ecosystem to give our members more choice and to offer advertisers a premium, better-than-linear-TV experience. We are looking for the founding members of this new business area for Netflix. The Ads Forecasting team builds the predictive foundation of the Netflix ads business — the models that tell us, before a campaign ever runs, how much inventory is available and how a campaign will deliver. We forecast supply and demand across audiences, ad products, and formats, and we predict campaign outcomes such as maximum availability, delivery confidence, reach, and frequency, accounting for the ad-serving optimizations that shape delivery. Our forecasts power media planning, underwriting, budget planning, yield, and the public API. This is a brand-new, foundational role. You will build the machine learning models that augment our simulation-based engine for predicting campaign delivery — turning a slow, rules-based simulation into fast, accurate, learnable models of how campaigns deliver against real inventory. You'll own the modeling and prototyping end-to-end and partner closely with our ML engineering team to take models to production. In this role, you will: - Build, prototype, and iterate on supervised machine learning models that predict campaign delivery outcomes — delivery risk, reach, frequency, and contention — to replace the current simulation engine. - Model demand-side campaign outcomes while incorporating supply-side signals , so the models reason about how well available inventory matches what advertisers are trying to achieve (targeting, frequency caps, contention, pacing). - Design rigorous offline and online evaluation frameworks to measure model accuracy, robustness to seasonality and distribution shift, and lift over the simulation baseline. - Own feature engineering and contribute to the team's feature store — turning ad-serving logs, campaign attributes, and supply signals into reusable, well-documented features. - Prioritize explainability and interpretability : your models' outputs must be defensible to sales and media-planning stakeholders making real booking and underwriting decisions. - Partner with ML engineers to deploy models at scale and to monitor production model health and drift , feeding monitoring insights back into the next modeling iteration. - Collaborate with cross-functional partners across product, engineering, and sales to define objectives, constraints, and trade-offs, and to drive adoption of ML-driven forecasts. - Communicate technical decisions, trade-offs, and results clearly to both technical and non-technical audiences at all levels of the company. We are looking for: - Advanced degree (PhD or Master's) in Statistics, Mathematics, Computer Science, or a related quantitative field. - 5+ years of relevant experience building machine learning models on large-scale data. - Deep expertise in supervised learning (e.g. gradient-boosted trees, regression, and related methods) with a strong bias toward interpretable, explainable models . - Strong feature engineering skills and familiarity with feature stores and standard ML lifecycle practice (versioning, evaluation, monitoring, retraining). - Proven ability to prototype algorithms and validate them rigorously against production data. - Strong programming skills in Python and strong SQL . - Working knowledge of ad-serving and campaign concepts — how campaigns are delivered and what creates delivery risk: targeting, frequency caps, contention, bidding, pacing, budget planning, and the core campaign objects/attributes; and the metrics that matter (reach, frequency, impressions, clicks, outcomes). You should understand both the supply side (ad-serving rules and inventory behavior) and the demand side (campaign attributes and advertiser goals). Ads experience is strongly preferred. - Ability to work independently, drive your own projects, and make compelling cases for prioritization. - Ability to communicate technical and statistical concepts clearly to audiences at many levels. - Embodies the Netflix values while bringing a new perspective to continue improving our culture. Nice to have: - Experience at a DSP, SSP, or publisher-side ad platform where predicting campaign outcomes at scale is a core science problem. - Familiarity with our ML stack (Metaflow) or comparable large-scale ML tooling. - Experience partnering with ML engineers to ship and monitor production ML systems. - Experience creating data products, dashboards, or explainability tooling for non-technical stakeholders. - Experience applying GenAI to boost developer/research productivity. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. At Netflix, we want to entertain the world, and we're constantly innovating on how entertainment is imagined, created, and delivered to a global audience. Increasingly, that innovation is powered by AI — and Netflix is making a deliberate bet to become AI Native, with AI woven into how we build products, create content, and run the company. The Opportunity The Agent Platform team gives Netflix engineers the infrastructure to go from zero to a production-grade AI agent without reinventing the wheel. We own the foundational building blocks the whole company builds on: the Model Gateway (unified access to external LLMs like Claude, GPT, and Gemini), the Assistance API for conversational use cases, the MCP Gateway that connects agents to Netflix's internal systems and knowledge, our Agent SDK, and an end-to-end evaluation stack. The work has moved well beyond chat completions. Teams across Netflix are now building agents — systems that plan, call tools, observe results, and iterate — and they depend on us for the infrastructure to do that reliably and to know whether their agents are actually any good. We're a small team with outsized leverage: what we ship becomes the foundation for AI across all of Netflix. What you will do: - Design, build, and operate the Agent SDK and MCP Gateway that Netflix engineers use to build, deploy, and run AI agents in production. - Build agents and agent infrastructure across the full lifecycle — plan/act/observe loops, tool and MCP integrations, deployment, and day-2 operations. - Make evaluation a first-class part of the platform: build the tracing, eval suites, and quality signals that let teams measure agents, catch regressions, and iterate to make them better. - Own reliability, observability, and guardrails for non-deterministic systems running at very high scale - Lead cross-functional initiatives with ML scientists, data scientists, product managers, and other AI Platform teams. - Rapidly iterate with users to improve the developer experience while establishing durable foundational capabilities. Desired Background: - 8+ years of software engineering experience with a track record of delivering quality results. - Hands-on experience building, deploying, operating, AND evaluating LLM agents in production — not just chat-completion apps or prototypes. - Experience with one or more agent frameworks/SDKs (Strands, OpenAI Agents SDK, Anthropic Claude Agent SDK, LangGraph, pydantic-ai, CrewAI, Google ADK) and with tool/function calling and MCP. - Experience with LLM/agent evaluation and observability — building eval suites, tracing, and quality measurement, then iterating on results (Braintrust, LangSmith, W&B, or equivalent). - Strong experience building SDKs and APIs for internal or external developers. - Strong fundamentals in building and operating scalable, observable, fault-tolerant distributed systems. - Proficiency in Python (and Python packaging tooling) plus one of Java, Go, C/C++, Rust, or Zig. Familiarity with our stack — Temporal, FastAPI, PostgreSQL, Kubernetes — is a plus. - Experience with large-scale build, release, CI/CD, and observability methods. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $466,000.00 - $750,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. We launched a new ad-supported tier in November 2022 to offer our members more choice in how they consume their content. Our new tier allows us to attract new members at a lower price point, while also creating a compelling path for advertisers to reach audiences that are deeply engaged. Our Team The Ads Platform Engineering teams build advertising systems and integrations that powers the delivery of ads using our world class content delivery ecosystem. We use a number of Netflix investments and innovations to power our ads - unique mix of client and server side ad insertions, state of the art content delivery system, ad encoding recipes, content understanding and metadata etc. We deliver ads in a manner that’s thoughtful of our member’s viewing experience and drive great outcomes for advertisers. We also ensure that advertiser brand safety is ensured during serving, members only see the most appropriate ads for them. About the Role We're looking for a Staff AI Engineer to join us as the first dedicated AI engineer. Your core mission is to build the AI infrastructure and agentic workflows that transform how our team develops and operates software. This is a greenfield opportunity. You won't be maintaining existing AI systems — you'll be designing and building them from scratch. Our team has active AI champions and early tooling already in production, but we need someone with deep hands-on experience to architect the foundational layer and accelerate our path to AI-native engineering. Our code footprint is reasonable today but expanding at an extraordinary pace; a core part of this role is striking the right balance between AI-driven speed and quality — shipping faster without accumulating slop, regressions, or accountability gaps. This role focuses on applied AI — building production systems with existing models and tools, not training LLMs. You'll leverage large language models, agentic frameworks, and retrieval-augmented generation to solve real infrastructure and product problems, with a direct impact on how quickly and confidently the team can deliver in a competitive market. What You’ll Do AI Infrastructure & Agentic Workflows - Architect and build a centralized context layer that gives AI agents grounded, team-specific knowledge - Design and implement agentic workflows for the full development lifecycle: AI-assisted code generation, automated test creation, PR pre-review, and deployment validation - Build AI-powered operational workflows — automated incident triage, log and metric correlation, root cause analysis, and guided resolution - Develop multi-agent orchestration where parallel agents handle implementation, testing, and documentation as coordinated workflows - Set up standardized AI development environments so every engineer can work in an AI-first workflow from day one - Drive team-wide AI adoption through hands-on enablement — pairing sessions, architecture reviews, workflow demonstrations, and continuous feedback loops Skills & experience we’re seeking: - 3+ years of significant  focus on applied AI systems - Proven experience building and deploying agentic AI systems in production — agent architectures, tool integration, orchestration, and evaluation frameworks - Hands-on experience setting up AI infrastructure for end-to-end software development workflows (AI coding assistants, context engineering, automated testing) - Strong software engineering fundamentals — you build production-grade systems, not just prototypes - Deep experience with retrieval-augmented generation — document indexing, embedding strategies, retrieval pipelines, and grounding techniques - Proficiency in Python and/or JVM languages - Demonstrated ability to drive technical adoption across a team — you can demonstrate value, build trust through pairing and architecture reviews, and bring engineers along on new workflows Nice to haves: - Prior experience as the first or early AI engineer on a team — standing up AI capabilities where none previously existed, with the ownership and initiative of an early-stage environment - Familiarity with LLM application patterns: context engineering, tool use / function calling, structured outputs, multi-agent coordination, and evaluation / hill-climbing methodologies - Experience integrating AI into CI/CD pipelines (automated PR review, test generation, deployment validation) - Background in building operational tooling — incident response automation, log analysis, diagnostic workflows Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $600,000.00 - $1,066,000.00. This compensation range will vary based on location. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here . Netflix is a unique culture and environment. Learn more here . Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. Job is open for no less than 7 days and will be removed when the position is filled.

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next. We are seeking a Senior Game Engineer who is passionate about the next frontier of interactive storytelling and player agency. In this role, you won’t just be building models; you’ll be building experiences. You will leverage Generative AI to break traditional scripted boundaries, creating dynamic gameplay systems that respond to players in ways previously thought impossible. Key Responsibilities * Design-Led Engineering: Work elbow-to-elbow with Game Designers to prototype and ship AI-augmented gameplay. * Player-Centric AI: Implement GenAI features that directly enhance the player experience, ensuring that AI-generated content feels intentional, high-quality, and most importantly, fun. * Core Systems Integration: Architect how GenAI hooks into core game systems (AI behavior trees, narrative engines, and world-building tools) to ensure seamless, low-latency performance. * Guardrails & UX: Develop the "logic layer" that sits between raw AI outputs and the player, ensuring content remains on-theme, safe, and balanced within the game's mechanics. * Rapid Gameplay Iteration: Use GenAI to accelerate the "find the fun" phase of development, building internal tools that allow for faster level blocking, asset variation, and playtesting loops. * Technical Troubleshooting: Debug complex interactions where AI systems meet deterministic game logic, maintaining the stability of the live game environment. Qualifications * Gameplay Engineering Core: 5+ years of professional experience in game development. You have a deep understanding of game architecture, player controllers, and real-time systems. * Applied GenAI Skills: Proven experience using LLMs or Diffusion models to solve specific product problems. You know how to prompt, fine-tune, and chain models to get predictable results in an unpredictable game world. * Systems Thinker: You understand how a change in an AI's "personality" or "generation parameters" affects game balance and the overall player journey. * Technical Proficiency: Expert-level C++ or C# (Unity/Unreal) and a grasp of Python for tooling and data pipelines. * Passion for Innovation: You are excited by "impossible" design challenges and believe GenAI is the key to unlocking new genres of play. Generally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $280,000.00 - $400,000.00. Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here. Netflix is a unique culture and environment. Learn more here. Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner. We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.