About the job
The Technical Program Manager in this role will shape how AIMS builds emerging AI products for years to come. You'll operate across a genuinely diverse stakeholder map: engineering and applied science teams, product and partnerships, and external device and platform partners. Your job is to turn emerging AI capability into experiences members actually use.
Responsibilities
Drive early-stage, high-ambiguity programs spanning generative AI product experiences, new interaction modalities, and new discovery surfaces, from first concept through path to production — alongside mature, highly cross-functional initiatives within Engagement Intelligence.
Own planning and execution: set milestones, manage dependencies, and align engineering, applied science, product, and partnerships teams around a shared plan.
Bring structure to 0-to-1 work, operating in problem spaces where the architecture, requirements, and partnership models are still taking shape, without over-engineering the process.
Coordinate with external device, platform, and distribution partners on integration timelines, technical requirements, and joint delivery milestones.
Support content expansion into new formats and modalities as Netflix's catalog grows beyond traditional video.
Weigh technology, cost, and business priorities against each other, and help teams make the right tradeoff for the moment.
Apply working knowledge of the ML project lifecycle, online and offline, to help teams plan realistic paths from prototype to production.
Build the lightweight program rituals — roadmaps, status updates, risk reviews, launch readiness — that keep fast-moving programs visible and on track.
Turn complexity into clarity: write the status updates, decision docs, and alignment artifacts that keep everyone from engineers to senior leadership on the same page.
Qualifications
Minimum
8-10+ years in technical program management or equivalent roles, with a track record driving multi-team, ambiguous programs at senior scope.
A track record building alignment and driving decisions across a broad stakeholder map, internal and external, without relying on formal authority.
Comfort operating in high ambiguity, bringing structure to 0-to-1 efforts where the architecture, requirements, and partnership models are still being defined.
The judgment to weigh technical, business, and cost tradeoffs and know which one should win.
Working knowledge of the ML project lifecycle, including online and offline stages, and what it takes to move a capability toward production.
Excellent written and verbal communication, with a track record of producing clear, decision-ready documents for audiences from engineers to senior leadership.
Preferred
Experience with generative AI product development.
Experience with search, discovery, or conversational/voice product programs, including coordination with external partners on path-to-production and joint delivery.
Experience supporting content or catalog expansion into new formats and modalities.
Background at a consumer-scale company with AI-driven products: streaming, social media, marketplaces, search, or voice/conversational products.