Software Engineer 5 - Platform Data Products

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 Role

Netflix operates one of the largest cloud infrastructure footprints in the world, and an increasing footprint of GenAI tools and agents. Platform Data Science & Engineering (Platform DSE) is an internal-facing team that helps Netflix's Technology org understand and optimize its cloud and AI infrastructure. 

We're looking for a full stack engineer to join our diverse team of analytics, data, and software engineers. In this role, you will focus on building products that enable Netflix to improve the efficiency of our Cloud and AI infrastructure.

You'll partner directly with engineering stakeholders to design and implement interactive web applications, backend services and APIs, agents and agent-facing tooling, analytics datasets, and integrations to microservices across Netflix. You'll become a domain expert in areas ranging from cloud infrastructure efficiency and coding agent "tokenomics," to GPU efficiency and enterprise-scale AI platform concerns.

You should have a background in relational data modeling, API design, and data-rich application development. You should have a strong sense of product ownership, and experience taking products from scoping, to design, to implementation.

What You'll Do

• Build and ship full stack features for our infrastructure cost and usage tooling, from the React and TypeScript frontend through the GraphQL services behind it.

• Help build and launch our product for analyzing AI productivity, cost and usage including designing the architecture, help shaping the data model, and build the tooling

• Contribute into other internal tooling surfaces (e.g. developer platform, ML/AI platform tooling) by contributing pertinent data produced from our team

• Build reusable components and shared infrastructure to enable our visualization and analytics engineers

• Partner with analytics engineers and data engineers on the data models behind these products. You won't build the pipelines, but you need to reason about them.

What We're Looking For

Must have:

• You've designed, built, and shipped full stack applications

• Experience contributing to internal systems and tools you don't own, including autonomously onboarding to new application stacks, strong design and architecture judgment, and proactive collaboration and communication

• Strong TypeScript and React, plus enough backend (Node.js, GraphQL, or similar) to own a data feature end to end

• Enough data fluency (SQL, and comfort reasoning about a data model) that a data-heavy product isn't a cold start. You don't need to be a data engineer, but you do need to be at home in messy, changing data.

• A track record of owning work on your own. You'd be our first software engineer, so you'll set direction and see it through without a big engineering org behind you.

Nice to have:

• GraphQL API design, or work with Druid, Iceberg, or similar analytics data stores.

• An interest in survey design or product analytics instrumentation, which is where AIPI may go next.

• You've worked closely with data scientists, analytics engineers, or data engineers on a small team.

Team and Culture

Platform Data Science & Engineering owns a wide slice of Netflix: infrastructure spend, developer productivity, traffic forecasting and experimentation, and availability. We value diversity of experience and background, direct ownership, and building durable products over one-off analyses. You'd work day to day with visualization engineers, analytics engineers, and data scientists, so you should be comfortable being the engineering voice in a room of data practitioners.

Netflix runs on people over process. We keep rules, approvals, and management layers light, and we trust well-informed people to make good calls (our "freedom and responsibility" model). For you that means real latitude and real accountability: you'll set technical direction and own how it turns out, not work a backlog someone else prioritized.