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About This Role
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.
As a Lead Product Manager (AI Platform), you will report into the Senior Manager, AI Platform, and serve as the senior technical IC inside a Product Engineering pod focused on translating internal stakeholder needs into shipped AI capabilities on the platform stack. You will own the path from initial stakeholder conversation through working system — scoping, building, evaluating, and graduating or retiring AI work end\-to\-end — and will set the technical direction for how the team prototypes and ships. You will operate independently of the standard sprint cycle, work directly with internal stakeholders without a PM intermediary, and influence adjacent engineers and PMs without managing them. This role is an individual contributor; mentorship of adjacent engineers and PMs is expected, but no direct reports.
What You'll Do
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- 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
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- 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.
The hiring range for this position in Orlando, FL $148,300 to $198,800 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job\-related knowledge, skills, and experience among other factors. 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/or other benefits, dependent on the level and position offered.
Salary Context
This $148K-$198K range is below the median for AI Product Manager roles in our dataset (median: $189K across 161 roles with salary data).
View full AI Product Manager salary data →Role Details
About This Role
AI Product Managers define what AI features get built and why. They translate business problems into ML-solvable tasks, work with engineering to scope model requirements, and own the metrics that determine if an AI feature is working. The role requires a rare combination of technical fluency and product instinct.
Unlike traditional product management, AI PM work involves managing uncertainty at a fundamental level. Your model might work 90% of the time. What happens the other 10%? What's the user experience when the AI is wrong? How do you measure 'good enough' for a probabilistic system? These questions don't have easy answers, and the AI PM is the person responsible for finding them.
Across the 3,823 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Disney Experiences, this role fits into their broader AI and engineering organization.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
What the Work Looks Like
A typical week includes: reviewing model evaluation results with the ML team, defining success metrics for a new AI feature, conducting user research on how customers respond to AI-generated outputs, writing product requirements that include accuracy thresholds and fallback behaviors, and presenting the AI roadmap to leadership. You're the translator between technical capability and business value.
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
Skills Required
Technical fluency with ML concepts is essential, though you won't be writing models. Expect to understand training data, evaluation metrics, model limitations, and responsible AI practices. SQL and basic Python are increasingly expected. Experience with A/B testing, data analysis, and product analytics is baseline. Understanding LLM capabilities and limitations is now a core requirement.
The differentiator is AI-specific product thinking: knowing when to use ML vs. heuristics, understanding the cost of training data collection, designing graceful degradation for model failures, and building products that improve with usage data. Experience with AI safety, bias mitigation, and responsible AI deployment is increasingly important.
Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
Compensation Benchmarks
AI Product Manager roles pay a median of $213,800 based on 583 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($173K) sits 19% below the category median. Disclosed range: $148K to $198K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Disney Experiences AI Hiring
Disney Experiences has 1 open AI role right now. They're hiring across AI Product Manager. Based in Orlando, FL, US. Compensation range: $198K - $198K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 median).
Career Path
Common paths into AI Product Manager roles include Product Manager, Data Analyst, Technical Program Manager.
From here, career progression typically leads toward Director of AI Product, VP Product, Head of AI.
The most effective path is PM experience plus self-directed AI education. Take Andrew Ng's courses, build a small ML project, and learn enough Python to read model evaluation code. The goal isn't to become an ML engineer. It's to have credibility in technical conversations and to understand what's possible, what's hard, and what's a bad idea.
What to Expect in Interviews
AI interviews typically combine coding challenges (Python-focused), system design questions tailored to the role, and discussions about your experience with relevant tools and frameworks. Strong candidates demonstrate both technical depth and the ability to make pragmatic engineering tradeoffs. Prepare portfolio projects that demonstrate end-to-end capability rather than isolated skills.
When evaluating opportunities: Strong postings describe specific AI products the PM will own, mention the ML team structure, and talk about measurement methodology. Look for companies that have already shipped AI features. Roles at companies that are 'exploring AI' often mean you'll spend a year defining the strategy before any building happens.
AI Hiring Overview
The AI job market has 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 roles).
AI Product Manager roles are growing as companies realize that shipping AI features requires different product thinking than traditional software. The best candidates combine product management experience with enough technical depth to have productive conversations with ML engineers about model capabilities and limitations.
The AI Job Market Today
The AI job market spans 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (112) are outnumbered by mid-level (1,798) and senior (1,516) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
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