below marketmost similar roles pay hereabove market
This role pays more than
99%
of similar roles. Most pay
$179,500–$255,000
— the blue band above.
At the midpoint, this role pays about
$833k
versus about
$217k
for comparable roles.
Based on 240 similar postings.
Employer
About Netflix
Netflix is the world''s leading streaming entertainment service, offering a vast library of TV series, films, documentaries, and original content to subscribers in over 190 countries. Industry: Streaming Entertainment & Media
Netflix currently has
179 open roles
on FindRole.
Listed pay typically runs
$436,000–$700,000
across 123 roles with salary data.
Member of Technical Staff, Agentic Systems - Games joins the Netflix Games team to lead the strategy, development, and delivery of GenAI tools and agentic systems. This role involves identifying AI opportunities, defining product roadmaps, and building production-grade systems including multi-step reasoning pipelines, tool-use agents, and multi-agent orchestration. You will prototype and ship features that transform player experience and team productivity by connecting frontier models to game engines and platform APIs. Key technologies include Python, LangChain, LangGraph, AutoGen, and Google ADK, alongside techniques like DPO, LoRA/QLoRA, and RLHF. You will also design evaluation infrastructure, including automated scoring and A/B testing. The work focuses on creating reusable agent primitives and infrastructure to solve complex technical challenges across game studios and platform teams.
Define the product strategy and architecture for GenAI tools and agentic systems across Netflix Games.
Create product roadmaps by deriving insights from user research and quantitative data to identify high-return investments.
Prototype and ship production-grade agentic systems including multi-step reasoning pipelines and multi-agent orchestration.
Build code harnesses and shared agentic libraries to connect frontier models to game engines and platform APIs.
Iterate on model capabilities through fine-tuning techniques like DPO, LoRA/QLoRA, and RLHF to improve performance.
Establish AI evaluation disciplines including offline scoring pipelines, A/B testing, and production telemetry for behavior drift.
Collaborate with engineering teams to scale model inference, data pipelines, and responsible AI safety guardrails.
Manage a small team of engineers to execute on AI product strategy and technical development.
What we're looking for
7+ years of experience in AI product strategy, machine learning, and AI engineering with a strong hands-on engineering foundation.
3+ years of experience in the game development industry.
Experience in games or interactive entertainment, shipping game features, working in game engines (Unreal, Unity), or building AI experiences for players.
Product management experience identifying user needs, defining product roadmaps, and running production development workstreams.
Deep, practical experience building and deploying agentic AI systems in production, including multi-step reasoning, tool use, and multi-agent orchestration.
Strong Python engineering skills and production experience with agentic frameworks like LangChain, LangGraph, AutoGen, or Google ADK.
Proven experience designing and operating evaluation infrastructure for AI systems, including offline benchmarks and automated scoring pipelines.
Familiarity with Model Context Protocol (MCP) or similar agent-to-system connectivity standards (preferred).
Unreal Engine 4
Unreal Engine 5
C++
Behavior Trees
Pathfinding
Perception Systems
State Machines
Root Motion
Distance Matching
Motion Warping
Blend Spaces
C#
Python
Build Automation
Game AI Architecture