EngineeringLead
Member of Technical Staff, Agentic Systems - Games
NetflixPosted Aug 12, 2026Netflix Games is hiring a technical leader to shape the strategy and hands-on delivery of GenAI tools and agentic systems across its game studios — a builder-PM hybrid who prototypes fast, ships production agentic systems, builds reusable agent infrastructure and MCPs, and manages a small team of engineers.
Salary
$600,000 – $1,066,000 / yr
Location
Los Angeles, CA
Work mode
—
Seniority
Lead
Compared with 43 other Engineering roles: Common across similar roles Unique to this role
What you'll do
Responsibilities
- Identify where AI adds value across Netflix Games, defining product strategy and architecture for new enablement systems
- Derive insights from user research and quantitative data to build roadmaps that distinguish hype from valueUnique
- Prototype fast to validate ideas, then take features from concept to production without a handoff layer
- Engineer production-grade agentic systems: multi-step reasoning pipelines, tool-use agents, multi-agent orchestration, and autonomous workflowsCommon
- Build reusable agent primitives, MCPs, and shared agentic libraries that reduce duplicated effort across studios and platform teams
- Iterate on model capabilities where needed: fine-tuning, DPO, LoRA/QLoRA, and RLHF for long-horizon agentic tasks
- Define AI evaluation as a first-class discipline: offline eval sets, automated scoring, regression gates, A/B testing, and drift detection
- Partner with external researchers and companies pioneering agentic AI
- Manage a small team of engineersUnique
What you'll need
Experience
- 7+ years in AI product strategy, machine learning, and AI engineering with a strong hands-on foundation
- 3+ years in the game development industry
- Product management experience: identifying user needs, defining roadmaps, running production workstreams
- Experience shipping game features, working in game engines (Unreal, Unity), or building AI experiences for players
- Deep practical experience building and deploying agentic AI systems in productionCommon
- Strong Python skills and production experience with agentic frameworks (LangChain, LangGraph, AutoGen, Google ADK, or equivalent)
- Proven experience designing and operating evaluation infrastructure for AI systems
- Deep understanding of the GenAI ecosystem: open models, infrastructure, safety frameworks, hosted vs in-house trade-offs
- Nice to have: MCP familiarity, inference optimization, responsible AI background, full LLM fine-tuning lifecycle, published research