Technical Program Manager 5 - AI for Member Systems

Netflix is a leading entertainment company on a mission to connect members with stories they'll love. They are seeking a Technical Program Manager to drive cross-cutting programs within the AI for Member Systems organization, focusing on AI-driven member experiences and ensuring effective collaboration across multiple teams.

Responsibilities:

• Drive Cross-Team AI Programs: Lead end-to-end coordination for complex, multi-team initiatives that span AI models, infrastructure, experimentation, and product integration
• Own Planning & Execution: Define and track milestones, manage dependencies, and ensure alignment across engineering, applied science, product, and infrastructure partners
• Navigate Ambiguity: Operate effectively in evolving problem spaces where requirements, timelines, and product definitions are still maturing—bringing clarity and structure without over-engineering process
• Manage Complex Stakeholder Maps: Work across multiple EMs, PMs, data scientists, and applied science leads to create accountability, surface risks, and drive decisions
• Establish Operational Excellence: Build and refine lightweight program rituals (roadmapping, status updates, risk reviews, launch readiness) that improve execution consistency and visibility for AI-heavy launches
• Bridge Product & Infrastructure: Connect the dots between product-facing teams and foundational/platform teams, ensuring AI capabilities are well-integrated and dependencies are managed
• Communicate Clearly: Produce concise status updates, decision documents, and alignment artifacts for stakeholders ranging from engineers to senior leadership

Requirements:

• 6–8+ years in technical program, engineering, or product roles, with significant time as a TPM or equivalent driving multi-team programs
• Background working within large engineering organizations on complex programs with both infrastructure and product components
• Proven ability to work across engineering, science, PM, and data teams in ambiguous contexts—building alignment and driving decisions without formal authority
• Excellent written and verbal skills; able to produce clear status updates, decision docs, and alignment artifacts for diverse audiences
• Ability to engage credibly with technical teams and understand system-level trade-offs, even if not writing code yourself
• Familiarity with AI/ML systems—recommender systems, search/ranking, experimentation, or LLM/GenAI productization
• Background at consumer-scale companies with AI-driven products (streaming, social, marketplaces, ads)
• Experience launching new content verticals or navigating high-ambiguity product spaces
• Exposure to LLM post-training (fine-tuning, RLHF/RLAIF, evals) or central ranking/relevance teams
• Comfortable in high-autonomy environments; skilled at building lightweight structure without over-engineering process