Lead Staff Engineer, GenAI & Agentic Systems for Games

Workman Labs; Los Angeles (CA); Hybrid; USD 600.000 - 1.066.000; Vollzeit

Zusammenfassung

Netflix Games is seeking a senior 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.

7+ years in AI product strategy, machine learning, and AI engineering with strong hands-on experience, plus 3+ years in game development.

Qualifikationen

• 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 production.
• 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.

Aufgaben

• 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 value.
• 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 workflows.
• 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 engineers.

Kenntnisse

AI product strategy

Machine learning

Python

AI engineering

Team leadership

Product management

Tools

LangChain

LangGraph

AutoGen

Google ADK

Jobbeschreibung

Member of Technical Staff, Agentic Systems - Games

Netflix 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.

$600,000 – $1,066,000 / yr

Location

—

Seniority

Lead

Compared with 49 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 value Unique
• 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 workflows Common
• 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 engineers Unique

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 production Common
• 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