Tech Lead Manager, GenAI Sandbox & Tooling (AI Foundations)

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.

Fast-paced innovation in large language models (LLMs) and generative AI is reshaping personalization and discovery at Netflix. We are building an in-house “Member LLM”, customized on Netflix data, and believe it will unlock a new class of personalized, interactive member experiences. 

While other teams within AI Foundations focus on model training, model evaluation, and data curation, the newly created GenAI Sandbox and Tooling team exists to accelerate learning and adoption through rapid experimentation and agentic system development. This team builds sandboxes, agentic systems, and high-fidelity internal demos—backed by lightweight infrastructure (sandboxed APIs, UIs, and integration patterns) that expose Member LLM internally for hands-on exploration—without the overhead of full productionization.

We are looking for a senior hands-on engineering leader to build and scale this team. This is a high-velocity, hands-on role at the intersection of systems engineering, GenAI application patterns, and foundation models, designed to bridge model development and downstream productization.

This role can be scoped as either an L6 IC Team Lead or an Engineering Manager, depending on background. In both cases, success looks like standing up a small, highly effective team that can rapidly build sandboxes, agentic systems, and internal demos—while partnering closely with foundation model teams, platform teams, and cross-functional product pods.

The GenAI Sandbox and Tooling team provides the environment for the organization to "touch and feel" our latest AI capabilities. Strategic questions include:

• How can we provide a stable, side-by-side sandbox for internal teams to qualitatively explore our in-house models against frontier models? 

• What agentic architectures (memory, state management, tool-calling) are most effective for future member-facing generative experiences? 

• How can we create polished, high-fidelity demos that build intuition for leadership without the overhead of full productionization? 

• From a tooling & software engineering perspective, what are the optimal integration patterns for application teams to consume custom-trained LLM models in a robust way?

• Lead with a Player-Coach Mindset: Provide technical leadership, architecture, and roadmap direction while remaining hands-on in the development of prototypes and tooling.

• Drive Rapid Exploration & Execution: Lead the development of agentic systems and internal sandboxing tools (UIs/APIs) with short, high-velocity iteration cycles.

• Bridge Research and Application: Partner closely with the Member Foundation Models team to expose their training progress via "shadow testing" and qualitative signal gathering.

• Own the GenAI Sandbox ("Canvas"): Own the creation of the foundation model (i.e. “Netflix Member LLM”) playground and MCP servers for complex tool use, partnering with the broader Netflix GenAI platform.

• Collaborate Cross-Functionally: Work with the cross-functional GenAI pod to "graduate" successful prototypes into production-level experiments and member-facing betas.

• Technical Leadership: Proven track record of leading technical teams or complex projects, ideally in a "player-coach" or lead capacity.

• Software Engineering Excellence: Strong background in full-stack or systems engineering, with the ability to build internal-facing APIs and UIs rapidly.

• LLM & Agentic Systems: Deep understanding of LLM application patterns, including prompt engineering, orchestration frameworks (memory/state), and tool use.

• Velocity-First Mindset: Demonstrated ability to balance "quick-n-dirty" prototyping for learning with the technical judgment to build robust integration patterns for others.

• Strong Communication: Ability to translate complex algorithmic capabilities into intuitive demos for leadership and partner teams

• 8+ years of experience in software engineering, with 3+ years in a technical leadership or management capacity.

• Prototyping Background: Experience building agentic architectures or high-fidelity prototypes that informed significant product or research bets.

• Experience with LLM-Ops: Familiarity with lightweight tooling for exposing and monitoring LLMs in a robust way.

• Hybrid Leadership: Experience acting as an L6 IC Team Lead or a people manager in a research-adjacent engineering environment.

• Full-Stack Proficiency: Ability to rapidly build and deploy internal-facing UIs and APIs to showcase model capabilities to non-technical stakeholders.

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. Learn more here.

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. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service.

Job is open for no less than 7 days and will be removed when the position is filled.