Manager - Applied AI

Overview At Disney, we’re storytellers. We make the impossible, possible. The Walt Disney Company is a world‑class entertainment and technological leader. Walt’s passion was to continuously envision new ways to move audiences around the world—a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences — and we’re constantly looking for new ways to enhance these exciting experiences. The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross‑company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. Team Description Disney’s Applied AI Acceleration team embeds directly with our businesses to turn AI possibilities into shipped solutions. We prototype fast, solve real problems, and build the internal capability that makes it stick. If you want to build things that actually change how Disney operates, this is your team. What You’ll Do We are hiring a Manager, Applied AI to join our Team! This role will be on‑site at least 4 days per week for teamwork and collaboration. This role will be responsible for building a team of AI‑native builders: engineers who treat Claude, Cursor, and whatever comes next as native collaborators; run a squad of 2–4 team members inside Disney’s Applied AI Acceleration practice, taking ambiguous problems from our business partners and shipping AI‑powered products that move the needle. What matters most is that you speak and think in user problems and AI solutions. This isn’t about building fast for its own sake. It’s about knowing you’re building the right thing for the user. Engineers who know product are great. Product ninjas who know how to build are great. What we care about is that you deliver value to the business teams who need it most. You're insatiably curious, a high collaborator, constantly building at the frontier, and you lead by doing. This is a player‑coach role; you’ll be in the codebase with your team, shipping alongside them. Responsibilities End‑to‑end delivery of 2–4 concurrent AI engagements with different cadence – some get scoped and shipped in days; others take weeks. Stand up a squad of 2–4 builders – Applied AI Engineers, a Squad Anchor or partnership with the Principal Applied AI Engineer, occasional Data Engineer or TPM pairing. Review PRs in the codebase, pairing on hard problems, picking up Cursor and working through the stuck parts. The opening of every engagement: finding the real problem underneath the stated one, proving feasibility fast, and deciding what’s worth shipping. Stakeholder relationships across all levels of the organization – translate between business outcomes and technical tradeoffs without losing nuance in either direction. Pattern extraction. Every engagement yields at least one reusable component, playbook, or template that the practice can deploy on the next one. Required Qualifications & Skills Minimum 8+ years of relevant experience. Minimum 2+ years’ experience in a leadership‑adjacent role: Engineering Manager, Technical Lead, Consulting Engagement Lead, Solutions Engineering lead, or equivalent. Experience with delivery of AI‑powered products end‑to‑end. LLMs, agents, embeddings, classical ML. Working fluency with the modern AI application stack – in production: prompt design, RAG, tool‑calling agents, eval harnesses. Data literacy. SQL, APIs, basic transformations. Enough to unblock yourself when an engagement stalls on a data question instead of waiting for the Data Engineer. Experience leading people – direct reports, tech leads and/or engagement teams. Preferred Qualifications Experience building AI products without a dedicated engineering team backing you (e.g., startup founder, solutions engineer, solo‑PM who ships). Prior experience with enterprise‑scale data and legacy systems. Experience with golden datasets, trace analysis, LLM‑as‑judge. Education Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience. #J-18808-Ljbffr