Staff Software Engineer – Context Enablement

Productivity Engineering is an AI-native organization tasked with making Netflix engineers more effective.We build and support the infrastructure to create, build, test, deploy, run, and observe the Netflix stack, with a central focus on how

AI changes how engineers work

the tools, context, evals, and paved roads that make agentic development reliable at scale. As Netflix grows, so does the complexity behind our engineering systems.

Our challenge is deceptively simple

keep the developer experience excellent even as complexity increases. Our work impacts virtually every engineer at Netflix and enables other platform teams to innovate faster.

The Agent and Engineer Experiences organization exists to make agents more capable, trustworthy, and easier to manage at scale. We also focus on how engineers and agents work together in practice: from plugins which deliver context to the developer experiences where engineers discover, trust, and use agents. We operate with a bias to action in a fast-moving space: shipping incrementally, learning from production, and exercising strong judgment as models, tools, and practices change.

Who we are

The Context Enablement pod owns the context layer that grounds coding agents in how Netflix works. Agent quality depends on plugins and curated knowledge; that layer is now business critical for engineering productivity and is growing faster than the governance around it.

We are responsible for

• The agent plugin ecosystem, how teams package and distribute agent plugins, MCP servers, and tools
• Dev Profiles, the standardized path for delivering the right tools and context to every engineer's environment
• NECP (Netflix Engineering Context Provider), the curated knowledge system grounding coding agents in Netflix-specific frameworks and patterns

We serve context producers (platform and domain teams authoring context) and consumers (engineers whose daily agentic work depends on it). We are building toward a Context Development Lifecycle across creation, evals, distribution, and observability so domain owners can manage their curated context while the platform handles the rest.

We are hiring a Staff engineer to serve as the technical lead for this pod: accountable for technical outcomes, farming for dissent across partners, and making clear judgment calls when the space shifts. You will set technical direction for a team of 4+ engineers and work shoulder to shoulder with the pod's EM, PM, and the organization's Architect to turn an ambiguous, fast-moving space into durable platform work. This is a new team in a new space; this role will be central to bootstrapping how we deliver context and how it connects to the broader engineer and agent experience at Netflix.

What you will do

• Shape how Netflix delivers, evaluates, and governs agent context across plugins, Dev Profiles, and NECP, with a bias to action and incremental delivery in production.
• Exercise judgment under change: stay current on the AI landscape, separate signal from hype, and translate what matters into durable platform improvements for Netflix engineers.
• Define and evolve technical strategy for the context platform as tools, models, and organizational needs shift.
• Partner with platform and domain teams to enable context producers to improve the daily agent experience for consumers.
• Establish feedback loops early: engage customers, measure quality and adoption, and iterate based on what you learn in production.
• Operate with agility when requirements are ambiguous: socialize options, decide, align partners, and adjust course as you learn.
• Make thoughtful technical and product tradeoffs in a fast-moving AI space.
• Lead and grow a team of 4+ engineers as their technical lead: set the technical bar, mentor through design and code. You believe deeply in mentoring as a multiplier for team quality and velocity, not an optional extra, and you will also share that impact across the org.

What we'll expect from you

• Prior experience leading large and/or cross-functional projects or product domains in a large engineering organization (500+ engineers).
• Prior experience on a team that builds tooling for other engineers (Developer Productivity, Platform, Engineering Effectiveness, or similar).
• Deep, hands-on expertise with agent context, plugins, and evals; strong fluency with modern agentic development practices and curiosity about where the space is headed.
• Demonstrated judgment under change: you adapt quickly, make sound tradeoffs without perfect information, and improve your approach as tools and constraints evolve.
• Track record of influence across teams without authority: standards, contracts, or paved paths other groups adopt.
• Examples of positive impact outside your immediate team (efficiency, quality of life, user sentiment, measurable adoption).
• Proficiency in Java/Kotlin/Go or JavaScript/TypeScript.
• Strong product engineering mindset: empathy for peers and customers, clarity on who benefits from your work and why now vs later.
• Comfort with ambiguity, incremental delivery, and continuous learning from production signals.
• A track record of technically leading and mentoring a team of engineers (formally or as a tech lead), with genuine belief in the value mentoring brings and evidence you have raised the bar for those around you.

Nice to have

• Prior experience with Internal Developer Platforms (IDPs) where engineers discover tools, documentation, and agent workflows in one place. Our sister team works on Console, Netflix's Developer Portal, a primary place where engineers interact with agents.
• RAG/vector DB experience (Pinecone, Weaviate, pgvector).
• Backend / distributed systems experience.

You will be successful in this role if you

• Are comfortable with ambiguity and enjoy problems where the solution still needs to be defined; you drive alignment and decide when consensus is unclear.
• Have a deep sense of ownership and pride in shipping reliable, customer-focused platform work.
• Communicate clearly in writing and conversation, including with partners who are new to agent context and evals.
• Proactively solicit and act on feedback from customers and colleagues.
• Seek what is best for Netflix and help colleagues across teams succeed.
• Are a self-starter: curious, biased to action, and willing to learn in public as the space keeps moving.

What to expect from us

• High-impact work that touches how engineers across Netflix build software with agents at the center.
• Stunning colleagues with diverse perspectives who value candid feedback and collaboration.
• A fast-moving AI space where judgment, agility, and learning in production matter as much as architecture.
• Meaningful growth through everyday feedback and ownership of real outcomes.
• Our culture is unique, and we live by our values, so it is worth learning more about Netflix culture.