Member of Technical Staff, Agentic Systems - Games

Workman Labs; Los Angeles (CA); Hybrid; USD 600,000 - 1,066,000; Full time

Job summary

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.

Qualifications

• 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.

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.
• 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.

Skills

AI product strategy

Machine learning

Python

AI engineering

Team leadership

Product management

Tools

LangChain

LangGraph

AutoGen

Google ADK

Job description

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 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 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