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About This Role
We're looking for a Lead Product Manager, Enterprise AI and Automation to define how Marqeta identifies, governs, and scales AI and automation across the organization, focusing on the internal enterprise platform and employee\-facing tooling to drive value across Marqeta's internal operations and employee experience.
You'll collaboratively design the AI vision for the enterprise, partner to build the governance and adoption frameworks that make it real, and work hands\-on to evaluate tools, run pilots, and drive measurable business value. You'll partner closely with business unit leaders, the AI Steering Committee, and BT engineering to ensure AI initiatives are prioritized against the highest\-impact problems — and that what gets built is driven to adoption.
This is not a research role or a strategy\-only role. The right person is equally comfortable presenting an AI governance framework to the executive team and rolling up their sleeves to configure an agent, evaluate a vendor, or run a pilot with a business unit.
We work Flexible First. This role can be performed remotely in the United States, only in one of our National locations, which you can review here.
The Impact You'll Have
- Enterprise AI \& Automation Strategy
+ Collaboratively define Marqeta's Enterprise AI \& automation strategy, including responsible AI principles, governance frameworks, and a multi\-quarter adoption roadmap.
+ Partner across the business to identify and prioritize high\-value AI and automation use cases for each business unit.
+ Map how work flows across the enterprise to identify where AI can deliver step\-change improvements — not just incremental automation, but fundamentally better ways of operating.
+ Define functional and technical requirements (FRD/TRD) for all internal AI/automation platforms, serving as the primary proxy for the BT engineering team.
Partner with Architecture Review Boards and AI Steering Committee to ensure all AI platforms and solutions adhere to defined IT standards and governance frameworks.
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- Demand Management \& Prioritization
+ Design and lead the Plan and Commit process with business stakeholders for AI and automation technology requests.
+ Define criteria for prioritizing automation projects and enhancements based on strategic alignment, risk reduction, ROI, and operational impact.
+ Conduct feasibility assessments and cost\-benefit analysis for proposed AI initiatives.
+ Prioritize the AI portfolio strategically against business outcomes and executive guidance — and hold the line on priorities to ensure engineering time is focused on the highest\-impact work.
Maintain a visible backlog of active and pending AI and automation initiatives, giving stakeholders transparency into status, effort, and expected value.
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- IT Product Delivery
+ Oversee QA and UAT processes to ensure systems meet business requirements before deployment.
+ Participate in sprint demos and provide feedback to ensure development meets defined acceptance criteria.
+ Coordinate deployment windows to minimize business disruption and risks.
+ Establish hypercare programs for major system go\-lives, including elevated incident SLAs and daily status check\-ins during stabilization.
Develop Business Systems Product Management competencies across the BT organization to ensure consistent and high\-quality product practices across the BT organization.
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- Vendor and Platform Management
+ Evaluate emerging AI technologies and conduct pilots to validate applicability and business value before committing to scale.
+ Lead vendor selection and commercial negotiations in partnership with Procurement and relevant stakeholders, and own ongoing vendor management for all Enterprise AI tooling contracts.
Stay current on the rapidly evolving AI landscape — tools, models, and platforms shift constantly, and this role requires continuous learning to ensure Marqeta's strategy reflects what's actually possible today.
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- Rollout, Adoption \& Change Management
+ Own and execute the Enterprise AI rollout plan in partnership with Corporate Communications and Learning and Development, ensuring deployment is phased, governed, and adoption\-focused across all business units.
+ Drive change management for AI initiatives — the best solution is worthless if nobody uses it. Build the channels, rituals, and feedback loops that make AI visible and valued across the organization.
+ Establish and manage the internal AI organizational capability—including an AI Champion Network and Community of Practice—to drive centralized knowledge sharing, collective skill development, and accelerated, peer\-led adoption across all business units.
Define adoption metrics and post\-launch stabilization plans for all major AI deployments.
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- Measurement \& Governance
+ Design and own the Enterprise AI metrics framework; measure, report, and continuously improve the quantifiable business value delivered by the AI program.
+ Report progress and outcomes to the senior leadership on a regular cadence.
+ Establish governance guardrails that balance innovation velocity with responsible, compliant AI use — particularly important in a regulated fintech environment.
Who You Are
- 7\+ years in IT product management, with at least 2 years focused on AI or emerging technology products.
- A genuine understanding of AI capabilities — summarization, classification, generation, agentic workflows — and the ability to translate that into business strategy and concrete use cases.
- Experience building internal\-facing enterprise AI systems or platforms; you think in systems and adoption curves, not just features.
- Demonstrated experience managing product backlogs, defects, and enhancement roadmaps for enterprise applications or internal platforms.
- Strong prioritization instincts and the ability to make hard calls about what matters most in a fast\-moving, resource\-constrained environment. You think in terms of business outcomes, not activity.
- Demonstrated ability to influence without authority — across business units, finance, legal, and security stakeholders.
- Comfort operating hands\-on with AI tooling: you don't need to write production code, but you should be able to evaluate a platform, configure an agent, and troubleshoot when something isn't working.
- Experience with no\-code/low\-code AI platforms (e.g., Workato, or similar) is a strong plus.
- Change management experience — you know how to drive adoption, not just deployment.
- Fintech or regulated industry experience preferred.
Compensation and Benefits
Marqeta is a Flex First company which allows you to choose your best working environment, whether that be from home or at a company office. To support Flex First, we calibrate pay to a competitive value according to working location. Compensation is aligned according to three tiers within the United States:
- National: A baseline tier that applies to most of the geographic territory of the United States.
- Premium: Slightly elevated from the National tier, and oriented toward a narrower set of higher cost\-of\-living areas, such as Los Angeles CA and Seattle WA
- Premium Plus: A tier for the most expensive working areas, like the San Francisco Bay area and New York City.
Visit this page or consult with a Recruiter to determine which tier would be applicable to you.
When determining salaries, we consider several factors including, but not limited to, skills, prior experience, and work location. The new\-hire base salary range for this position is:
- National: $136,100 \- $170,100
We also believe in recognizing the contributions of our people. That's why we award annual bonuses to eligible employees, rewarding both individual performance and the success of the entire company.
Along with monetary compensation, Marqeta offers
- Multiple health insurance options
- Flexible time off – take what you need
- Retirement savings program with company contribution and after tax contributions
- Equity in a publicly\-traded company and an Employee Stock Purchase Program
- Family\-forming benefits, fertility support, and up to 20 weeks of Parental Leave
- Free therapy sessions, financial and professional coaching, and legal advice
- Monthly stipend to support our remote work model
- Annual "development dollars" to support our people growth and development
- Through Flex First, the freedom to live and work wherever you and your family thrive
#### About Marqeta
Marqeta is on a mission to change the way money moves. We're one of the earliest enablers of embedded finance, a market opportunity sized up in the trillions. Our card issuing platform provides unprecedented flexibility and control for companies to issue cards, authorize transactions, and manage payment operations in real time. Marqeta is powering the most well known brands in the new economy (Block, Cash App, Affirm, Instacart, Doordash, Uber, Walmart, etc). You don't need to be a Payments expert to join the Marqeta Team, let us help you with that. This is the opportunity of a lifetime to work with innovators around the world and unlock equitable financial access for all.
#### Marqeta's Values
– Solve for the Customer: With a deep understanding of our customers' business and empathy for their needs, we deliver products and services that drive their success. Earning and keeping their trust guides everything we do.
– Do What's Right: Knowing businesses and livelihoods depend on us, we pursue solutions that disrupt responsibly and deliver high\-quality results that our customers count on. We own our work from start to finish.
– Simplify and Innovate: We approach challenges with curiosity and take smart risks. Innovation comes from finding better, simpler ways to achieve extraordinary outcomes.
– Win as a Team: We succeed together by embracing diverse perspectives and pushing each other to raise the bar. We lead with humility and set aside hierarchy to work as a team.
– Make it Count: We drive forward with focus and agility. With a sense of urgency and purpose, we get the job done, and done right.
Equal Employment Opportunity, Accommodations and Privacy
Marqeta is an equal opportunity employer committed to an inclusive workplace that fosters belonging. We do not discriminate based on race, color, religion, sex (including pregnancy, lactation, childbirth, or related medical conditions), veteran status or uniformed service member status, age, national origin or ancestry, citizenship or immigration status, physical or mental disability, gender identity, gender expression, sexual orientation, genetic information (including testing or characteristics) or any other characteristic protected by applicable law. We also consider qualified applicants with criminal histories, consistent with legal requirements.
Marqeta endeavors to make reasonable accommodations for applicants with disabilities. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre\-employment testing, or otherwise participate in the employee selection process, please submit this form with your specific accommodation request.
Personal data that is provided as part of the application and recruitment process is processed in accordance with the Applicant Privacy Notice. Additional information for California residents can be found here.
Salary Context
This $136K-$170K range is in the lower quartile 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 Marqeta, 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 ($153K) sits 28% below the category median. Disclosed range: $136K to $170K.
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.
Marqeta AI Hiring
Marqeta has 1 open AI role right now. They're hiring across AI Product Manager. Based in Austin, TX, US. Compensation range: $170K - $170K.
Location Context
AI roles in Austin pay a median of $215,300 across 523 tracked positions. That's 8% above the national 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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