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Lead Product Manager, AI Platform

Job in Orlando, Orange County, Florida, 32885, USA
Listing for: 1976 Walt Disney Attractions Technology LLC
Full Time position
Listed on 2026-07-16
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 148300 - 198800 USD Yearly USD 148300.00 198800.00 YEAR
Job Description & How to Apply Below

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, Open Router, Bedrock, or equivalent), one workflow or agent runtime (n8n, Lang Graph, 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.
Pr…
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