Software Engineering 5 - Ads Agent (Agentic Platform for Enterprise)

Responsibilities

• Design and build core platform primitives - agent framework, tool/skill registry, orchestration runtime, memory and retrieval infrastructure, evaluation harness - that other domain teams use to build their own agents and skills.
• Define APIs/SDKs and integration patterns so domain teams can plug in their own enterprise (non-coding) use cases without rebuilding core agent infrastructure.
• Build and iterate on the platform's tool/function-calling framework, planning/orchestration layer, memory, and retrieval subsystems.
• Explore entity/knowledge graphs as a shared grounding/context layer that multiple agents on the platform can draw on.
• Partner with domain teams to understand their use cases and shape the platform's building blocks and roadmap accordingly.
• Own platform reliability, evaluation/observability tooling, and guardrails that other teams' agents inherit for free.
• Ship fast - take things from prototype to a platform primitive other teams can adopt, with tight iteration cycles.

Must-have qualifications

Real, hands-on GenAI experience in enterprise contexts

• not coding assistants or developer tools. Customer/partner-facing or internal process automation both count.

Experience building platforms, frameworks, or SDKs consumed by other engineering teams

• not just point solutions. This role is about building the thing other teams build on top of.

Demonstrated high shipping velocity

• a track record of building and launching new systems quickly and working comfortably with ambiguity. Backgrounds dominated by maintaining legacy systems are not a fit here.

• Strong software engineering fundamentals - production-grade systems, API/SDK design, backend engineering.
• Experience with agent-system building blocks: tool/function calling, orchestration, retrieval-augmented generation (RAG), prompt/context engineering.

Nice-to-have

• Experience with entity/knowledge graphs - modeling entities and relations, graph-based retrieval, graph databases, or graph-augmented RAG (useful as a shared grounding layer across agents on the platform).
• Experience with agent frameworks (SpringAI, LangGraph, LlamaIndex, AutoGen) or having built comparable orchestration frameworks in-house.
• Experience in ads/marketing tech.
• Familiarity with evaluation frameworks for LLM/agent quality.

Pay and benefits

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 $388,000.00 - $558,000.00.

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.

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.