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About This Role
Senior Product Manager, AI Enablement - Analytics: Capital One Shopping (Remote-Eligible) Come join our growing team in Capital One Shopping - the AI Enablement team builds and owns the AI products and platforms the rest of the organization runs on.
Product Management at Capital One is a booming, vibrant craft that requires reimagining the status quo, finding value creation opportunities, and driving innovative and sustainable customer experiences through technology. We believe our portfolio of businesses and investments in growth and transformation will result in a company with the scale, brand, capabilities, talent, and values to succeed as the digital revolution transforms our society and our industry.
We're looking for a Senior Product Manager with deep data platform experience to own Shopping’s agentic analytics platform. Applied AI experience is a plus, and we value candidates who are builders and actively use AI tools (e.g., Claude Code, Codex, Cursor) to prototype rather than specify, and who’d rather ship a PoC than write a doc about it. Show us what you’ve built.
Capital One Product Framework
In this role, you’ll be expected to demonstrate proficiency in five key areas which we consider to be the foundation for successful Product management:
- Human Centered - Obsesses about internal and external customer needs to reimagine and innovate product solutions
- Business Focused - Delivers game-changing outcomes by focusing on leverage and execution excellence
- Technology Driven - Leverages technology to deliver innovative and resilient solutions that enable both near term and long term value
- Integrated Problem Solving - Identifies and resolves complex problems to deliver outcomes while mitigating product risks
- Transformational Leadership - Leads cross functional teams to solve customer problems and drive organizational alignment
What we are looking for:
- Deep experience with enterprise data and how it’s defined and governed (semantic and metrics layers, data catalogs, ontologies, warehouse and BI, etc.)
- Familiarity with tools across the modern data stack (dbt, LookML, Snowflake, Databricks, Palantir Foundry, Looker, Mode, etc.)
- Familiarity with how AI agents work across structured data (text-to-SQL, tool use, evals, and where these systems fail)
- Someone who has adjudicated metric disputes and made the decision stick
- A builder who would rather be in the tools prototyping than be dependent on someone else to run them
- Comfort with backend and internal platform products, where the users are diverse business and technical teams, and the measure is whether they trust the outputs
- A strategic thought leader who can create a compelling vision and story to present to senior executives and inspire direct and partner teams
- A strong communicator who can advance initiatives and create consensus through clear, concise, and contextually relevant messaging
- Someone who works with minimal direction and a mandate that’s still taking shape
- Deep work experience handling large data files using SQL, Python, and/or R
What you’ll do:
- Partner with platform engineers to build and operate AI products that teams across Shopping depend on, starting with an agentic analytics platform
- Understand the enterprise data requirements and ensure the system’s compliance with enterprise patterns
- Define what a system needs to know to be trusted (the data, the definitions, the context behind both)
- Set the boundaries for what agents can and can’t do, and prove those boundaries hold in practice
- Relentlessly push to understand user and stakeholder needs and ensure they are considered in prioritization and trade-off discussions
- Make each successive deployment cheaper and faster than the last
- Build and maintain strong relationships with leaders and stakeholders that depend on the capabilities and performance of our platforms
- Define, socialize, and monitor key performance indicators to understand the evolution and success of the project
Basic Qualifications:
- At least 4 years of experience in Product Management, Solutions or Deployment Engineering, Technical Consulting, or Data Analytics experience
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: + A Bachelor's or Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field), Business or Marketing + OR + Bachelor's degree in any field and at least 4 years of Product Management, Solutions or Deployment Engineering, Technical Consulting, or Data Analytics experience
Preferred Qualifications:
- 7+ years of Product Management, Solutions or Deployment Engineering, Technical Consulting, or Data Analytics experience, including ownership of an internal platform or a production deployment into a real operating environment
- 4+ years of experience working directly in data, with a deep proficiency in SQL
- Experience defining and governing metrics across teams that did not agree
- Experience with semantic layers, metrics layers, or ontologies (dbt, LookML, Cube, Palantir Foundry, or comparable)
At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
Capital One is open to hiring a Remote Employee for this opportunity.
The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.
McLean, VA: $200,700 - $229,100 for Sr. Mgr, Product Management
New York, NY: $219,000 - $249,900 for Sr. Mgr, Product Management
Remote (Regardless of Location): $182,500 - $208,300 for Sr. Mgr, Product Management
Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at [email protected]. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.
For technical support or questions about Capital One's recruiting process, please send an email to [email protected]
Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.
Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
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 9,079 AI roles we're tracking, AI Product Manager positions make up 5% of the market. At Capital One, 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 $220,200 based on 947 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Capital One AI Hiring
Capital One has 112 open AI roles right now. They're hiring across AI/ML Engineer, AI Product Manager, Data Scientist, AI Software Engineer. Positions span New York, NY, McLean, VA, McLean, VA, US.
Remote Work Context
Remote AI roles pay a median of $188,000 across 2,316 positions. About 6% of all AI roles offer remote work.
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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 Safety roles lead at $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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.
Frequently Asked Questions
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