Job description

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. Machine Learning/Artificial Intelligence powers innovation in all areas of the business, from helping members choose the right entertainment for them through personalization, to better understanding our audience and our content slate, to optimizing our payment processing and other revenue-focused initiatives. Building highly scalable and differentiated ML infrastructure is key to accelerating this innovation. The Opportunity Agents are becoming a primary way software gets built and work gets done at Netflix — and the AI Platform is building the foundation they run on. The Agent Platform team owns the agent-specific layer that every agent at Netflix depends on: the runtime and execution environment, memory, identity and permissioning, discovery and registry, evaluation, and the tool/MCP interfaces agents use to act. We build the paved path agent developers across the company build on, and we operate the runtimes for the workloads the general platform can't reach — including at member scale. We're looking for a Senior Engineering Manager to lead this team. This is a small, senior, high-leverage group working at the front edge of a domain that is still being invented — where frameworks turn over in months and the durable bets are not obvious. The hardest part of this job is not the code — it is choosing what to build, and what will still matter once today's tools are gone. You will: • Own the charter and technical direction. Set the platform's technical strategy and roadmap — the agent-specific foundation every agent depends on, and the selective runtimes worth operating directly — and decide where to invest ahead of demand. • Lead and grow a high performing team. Hire, develop, and retain excellent engineers; set a high bar; and create the conditions for a small team to have outsized impact. • Make sharp build, adopt, or partner calls. Decide which capabilities the platform owns and which it draws from partner teams, define the interfaces between them, and keep a small team focused on the highest-leverage layer. • Turn the new hard problems into primitives. The most durable problems in this space are the ones that let agents get better from their own experience: capturing each run's full reasoning-and-tool-call trajectory as structured, replayable data; turning real-world outcomes into evaluation signal; memory that compounds across runs; and a feedback loop that turns that signal into improved behavior, promoted behind eval gates and safe rollout. Make these first-class platform capabilities with real contracts — so agents built on the platform measurably improve over time, not just scale. • Operate as part of the AI Platform leadership team. Set direction alongside peer leaders across the AI Platform and partner orgs, represent the team in senior technical forums, and build the cross-team alignment a foundational platform depends on. If you've built platforms and you know that the defining work is judgment — what to own, what to hand off, what to bet on while the ground is still moving — this is the role. Minimum Qualifications • Experience leading and growing engineering teams that build and operate platform or infrastructure at scale — managing senior individual contributors and/or managers, with a track record of developing strong engineers. • Hands-on experience designing, building, and operating agentic systems in production — agent runtimes and harnesses, tool use, memory, and evaluation — with genuine technical depth, not oversight from a distance. • Breadth across business applications: you've built or led agents spanning a range of use cases, enterprise and internal applications (developer tooling, operations, knowledge work) or consumer-facing applications at scale. • A strong engineering foundation in distributed systems, cloud, and ML/AI infrastructure — deep enough to lead a senior team's hardest architectural decisions and earn its trust. • A track record of owning a platform's charter — setting its direction and holding its scope against pressure to do everything — and making build-versus-partner decisions on a multi-year cost horizon. • Cross-organizational credibility: a record of building shared accountability with senior leaders across adjacent platform, infrastructure, and security teams, and navigating ambiguous ownership boundaries. • Strong written and verbal communication; comfort with ambiguity; able to lead both 0-to-1 and 1-to-100 work; effective across a distributed (US) team. Preferred Qualifications • Experience with the emerging class of agent concerns: agent identity and permissioning, guardrails and safety, and cost governance for LLM and agent workloads. • Experience running a platform that other engineers consume as a product — paved paths, migrations, deprecations, and developer experience. • Credibility in a relevant open-source ecosystem (agent frameworks, runtimes, or developer tooling). 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 $676,000.00 - $1,195,000.00. 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.

Requirements

Must-haves

Lead and grow a high performing team. Hire, develop, and retain excellent engineers; set a high bar; and create the conditions for a small team to have outsized impact.
If you've built platforms and you know that the defining work is judgment — what to own, what to hand off, what to bet on while the ground is still moving — this is the role.
Experience leading and growing engineering teams that build and operate platform or infrastructure at scale — managing senior individual contributors and/or managers, with a track record of developing strong engineers.
Hands-on experience designing, building, and operating agentic systems in production — agent runtimes and harnesses, tool use, memory, and evaluation — with genuine technical depth, not oversight from a distance.
A strong engineering foundation in distributed systems, cloud, and ML/AI infrastructure — deep enough to lead a senior team's hardest architectural decisions and earn its trust.
A track record of owning a platform's charter — setting its direction and holding its scope against pressure to do everything — and making build-versus-partner decisions on a multi-year cost horizon.
Cross-organizational credibility: a record of building shared accountability with senior leaders across adjacent platform, infrastructure, and security teams, and navigating ambiguous ownership boundaries.
Strong written and verbal communication; comfort with ambiguity; able to lead both 0-to-1 and 1-to-100 work; effective across a distributed (US) team.

Nice-to-haves

Experience with the emerging class of agent concerns: agent identity and permissioning, guardrails and safety, and cost governance for LLM and agent workloads.
Experience running a platform that other engineers consume as a product — paved paths, migrations, deprecations, and developer experience.
Credibility in a relevant open-source ecosystem (agent frameworks, runtimes, or developer tooling).
Netflix is a unique culture and environment. Learn more here .
Job is open for no less than 7 days and will be removed when the position is filled.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlaillm

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

401(K)

Paid Time Off