Senior Applied AI Lead, Talent
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.
Our Talent AI Team:
We are at a very exciting stage of evolution at Netflix . As we experience growth in our employee population, lines of business, geographical footprint, and workforce heterogeneity, it is imperative that the Talent function evolves accordingly to shape and support this progress. One of the most critical parts of this evolution is the foundation upon which we can scale personalized and inclusive experiences for the workforce.
Our Talent AI team is focused on helping to drive change at scale. The team is fundamentally helping to find ways to drive AI powered solutions in how we attract, develop, and retain the extraordinary people who power our business, while also helping to drive greater AI adoption and fluency across Talent. This team is critical in identifying, prototyping, and shipping AI-powered capabilities across the full Talent lifecycle. The team works closely with all functional areas across Talent — as well as Netflix 's central AI teams.
The Role:
We are looking for a Senior Applied AI Lead who can bridge the gap between Talent's biggest opportunities and what is possible with today's AI tools. This person can both envision high-impact solutions and build working prototypes that turn ideas into something stakeholders can actually touch and react to — before a single engineer is engaged.
This is not a traditional product manager role or an engineering role. It sits in the space between: someone with strong Talent domain expertise and genuine AI fluency who moves fast, exercises high judgment about what is worth building, and knows how to take a prototype all the way to a production partnership with engineering.
Responsibilities include, but are not limited to:
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Partnering with Talent teams to identify the highest-value AI opportunities.
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Defining problem statements, scope solutions, and prioritizing ruthlessly — distinguishing genuinely high-leverage AI applications from novelty.
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Developing a deep understanding of Talent's data landscape, workflow pain points, and strategic priorities to inform where AI can create durable impact.
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Designing and building working AI prototypes — from scoping the problem to putting a functional demo in front of stakeholders for validation.
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Use LLM APIs, agent frameworks, AI-native platforms, and workflow automation tools to rapidly iterate without requiring dedicated engineering resources.
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Translating validated prototypes into tight product requirements and partnering with engineering to move from proof-of-concept to production.
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Acting as the domain and product authority for Talent AI features in technical design discussions — bridging the gap between what Talent needs and what engineering builds.
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Owning outcomes, not just outputs — staying engaged through deployment and adoption to ensure the solution actually delivers value.
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Evaluating AI tools, platforms, and vendors with rigor — building a clear point of view on what to adopt off-the-shelf, what to integrate, and what to build custom.
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Staying current on the rapidly evolving AI landscape and translating new capabilities into practical Talent opportunities faster than our peers.
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Building the playbooks, prompting guides, and workflow blueprints that help Talent teams get genuine leverage from AI tools — not just familiarity.
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Developing other Talent team members' AI fluency through hands-on sessions, shared examples, and clear frameworks for when and how to use AI.
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Ensuring every AI solution is designed with appropriate data privacy, security, and fairness considerations — partnering with