Lead Product Manager, AI Platform

At Disney Experiences Technology, our team creates world-class immersive digital experiences for the Company’s premier vacation brands, including Disney’s Parks & Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club. We are responsible for the end-to-end Guest experience for all technology & digitally led initiatives across Attractions & Entertainment, Food & Beverage, Resorts & Transportation, and Merchandise lines of business, as well as AI-related innovation. This role sits within the AI Center of Excellence (COE) inside DX Tech & Digital, focused on building and scaling the internal AI Platform that powers next‑generation intelligent solutions across Disney Experiences. What You’ll Do Take internal stakeholder asks from initial conversation to shipped AI capability: owning discovery, scoping, design, build, and rollout end‑to‑end, without waiting for requirements to be handed down. Build AI‑native workflows on the internal AI Platform stack: prompts, agents, retrieval pipelines, evaluation harnesses, and the integrations that make them useful. Drive technical direction for the Product Engineering pod within the AI Platform team: setting prototyping standards, evaluation patterns, and shared tooling that the rest of the team builds on. Operate independently of the standard sprint cycle; make product and architecture decisions in a low‑structure environment, knowing when to cut scope, when to ship, and when to ask for input. Share work‑in‑progress at 70% complete to gather stakeholder feedback and iterate, rather than holding work until it’s polished. Instrument prototypes with eval frameworks to know whether a capability is earning its place; graduate, harden, or retire work deliberately based on what the data shows. Build prototypes, demos, and mockups that demonstrate AI capability to stakeholders, validate emerging platform patterns, and serve as reference implementations to future work. Mentor adjacent engineers and PMs on AI prototyping and outcome‑driven development; serve as the point of escalation for prototype‑stage work across the team. Influence cross‑team alignment with platform engineers, AI ops, security and compliance partners, and PMs, driving outcomes through influence rather than authority. Communicate technical tradeoffs and recommendations to senior stakeholders, connecting platform capability to measurable business outcomes. Basic Qualifications Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent years of work experience. 7+ years of combined experience across software engineering and product roles in technical or AI‑platform contexts. Production experience with LLM‑powered applications, including advanced prompt engineering, agent frameworks, evaluation pipelines, and retrieval‑augmented generation. Hands‑on technical capability sufficient to scope, build, and ship a working prototype end‑to‑end – comfortable in Python and modern AI tooling, able to operate without engineering or PM handoff. Demonstrated experience taking ambiguous stakeholder asks and returning working systems, comfortable talking to users directly, without waiting for a product manager to define requirements. Demonstrated history of taking products or capabilities from 0 → 1 inside an enterprise or platform environment, with measurable adoption outcomes. Hands‑on production experience with at least one LLM gateway (LiteLLM, OpenRouter, Bedrock, or equivalent), one workflow or agent runtime (n8n, LangGraph, Temporal, or equivalent), and one evaluation or observability framework (Arize, Phoenix, Langfuse, or equivalent). Demonstrated judgment in scope, speed, and quality tradeoffs: knowing when to ship at 70% to learn fast, when to harden, and when to retire work that isn’t paying off. Track record of driving cross‑team outcomes through influence without direct authority: coordinating with PMs, platform engineers, and adjacent engineering teams. Excellent communication skills, including the ability to translate AI capability into business outcomes for senior stakeholders. Preferred Qualifications Background as a forward‑deployed engineer, applied AI engineer, or product‑minded engineer in an AI‑native company or AI platform context. Direct production experience with MCP (Model Context Protocol), OpenWebUI, n8n, LiteLLM or similar tools within this space. History shipping deliberately scrappy prototypes for stakeholder learning, with the judgment to distinguish prototype scale from production scale. Familiarity with enterprise security, compliance, and governance patterns for AI systems. Experience instrumenting AI products with eval frameworks and AI observability tooling. Background partnering with non‑technical senior leaders to decompose business problems into shipped AI capabilities. Salary range: $148,300 to $198,800 per year. The base pay actually offered will take into account internal equity and may vary based on the candidate’s geographic region, job‑related knowledge, skills, and experience. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and other benefits, dependent on the level and position offered. #J-18808-Ljbffr