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Discover your future at Citi
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Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact.
Job Overview
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Services provides global solutions that help corporations, financial institutions, public sector and commercial clients optimize operations and drive their business forward. Through our five business lines – Liquidity Management Services, Payments, Trade \& Working Capital Solutions, Investor Services and Issuer Services \- we provide cash management, payments/receivables solutions, working capital solutions, post\-trade securities services and issuer services across Citi’s global network.
Citi is building the next generation of AI\-powered financial products across its global Services business. We are seeking experienced SVP\-level AI Product Managers to drive the execution of the AI product agenda within a specific business line — Payments, Investor Services, Issuer Services, or Trade.
This role operates at the heart of the business, working at the intersection of commercial product management, client engagement, and AI delivery. You will manage significant components of the Global AI Product roadmap for your business line — contributing to strategic direction, prioritizing use cases, and driving disciplined execution from concept through to commercialization. You will be expected to work with significant autonomy while maintaining close alignment with the Director\-level AI leadership above you.
What Makes This Role Distinct
This is a delivery\-focused, commercially\-accountable, client\-engaged role. Unlike the Director\-level position which is primarily strategy\-setting, this role is defined by:
- Hands\-on execution ownership — you are accountable for delivery plans, milestones, and outcomes, not just strategy
- Direct, day\-to\-day client engagement — you are regularly in the room with enterprise clients validating solutions and co\-creating products
- Use case ownership — you manage specific AI use cases end\-to\-end, from business case through to production and commercial launch
- Commercial discipline — you apply rigorous ROI\-thinking to every investment decision and track actuals against projections
- AI Risk Co\-ordination Establish and manage a consolidated AI risk framework for TWCS — coordinating across Model Risk Management, Operational Risk, Technology, and the Line of Business to maintain a live, actionable AI risk register.
- AI Testing \& Performance Define and own the AI testing strategy across the full model lifecycle — setting performance benchmarks, robustness protocols, and continuous improvement feedback loops tailored to trade finance use cases.
- AI Governance \& Implementation Design and implement a fit\-for\-purpose AI Governance framework — embedding model lifecycle policies, committee structures, and governance controls into Agile delivery workflows, aligned to Citi enterprise standards and emerging regulatory mandates.
- Explainability \& Audit Readiness Embed Explainable AI (XAI) solutions across TWCS AI use cases and ensure all models are perpetually audit\-ready — maintaining comprehensive model documentation, data lineage artefacts, and regulatory compliance controls.
- Market Intelligence \& Program Management conduct structured market research to identify AI\-driven opportunities — translating external signals, client needs, and competitive dynamics into actionable product AI programs.
- AI Use Case Development Define, structure, and prioritize AI use cases across the product and sub product portfolio — ensuring each use case is grounded in client value, commercial viability, technical feasibility, and risk acceptability.
- Post Ops process design and drive how operation process changes after AI is deployed.
- AI Product Ecosystem Build and manage the AI product ecosystem — cultivating partnerships with technology providers, internal platforms, and external innovators to create a coherent, interoperable foundation for AI\-powered trade finance products
Key Responsibilities
AI Product Roadmap \& Execution
- Own and drive significant workstreams within the Global AI Product roadmap for your business line — translating strategic priorities into detailed delivery plans, managing milestones, and driving cross\-functional execution from concept through commercialization
- Prioritize the AI use case backlog based on ROI, strategic fit, and client demand — maintaining a clear, well\-groomed product backlog that aligns business objectives with engineering execution
- Balance innovation ambition with business pragmatism and P\&L accountability
Client\-Facing AI Products
- Identify, scope, and drive the delivery of AI\-powered capabilities that create differentiated value for clients — such as intelligent payment orchestration, predictive receivables management, anomaly detection, and personalized client insights
- Engage directly and regularly with enterprise clients to validate solutions, gather requirements, manage expectations, and co\-create products
- Define clear go\-to\-market plans for AI products, managing the full lifecycle from initial prototype to commercial launch
Commercial Discipline \& Business Case Management
- Develop business cases and ROI analyses for AI initiatives — modelling cost and revenue scenarios, tracking actuals against projections, and presenting investment recommendations to senior stakeholders
- Evaluate all AI opportunities through a rigorous commercial lens, ensuring every initiative drives measurable financial outcomes
- Contribute to P\&L reporting and commercial performance tracking for your AI product portfolio
Internal AI Adoption
- Drive the structured identification and deployment of AI tools that enhance internal operations and team productivity across your business line
- Champion responsible AI adoption — acting as the primary internal advocate for AI literacy and culture change
Responsible AI \& Enterprise Controls
- Ensure all AI capabilities are built in line with Citi's enterprise risk standards — coordinating model risk governance, data lineage documentation, explainability requirements, and regulatory compliance controls
- Proactively identify and escalate ethical AI considerations to senior stakeholders
Stakeholder Management \& Global Delivery
- Cultivate effective working relationships across Sales, Technology, Operations, Finance, Compliance, Risk, and Legal — facilitating alignment across competing priorities
- Manage the geographic rollout of AI capabilities across multiple markets, adapting solutions to local regulatory requirements while maintaining global design consistency
Who We're Looking For
Required
- 8\+ years of product management experience, including demonstrated delivery of large\-scale, technology\-led products
- Proven experience building, launching, or scaling AI/ML\-powered products or digital platforms, ideally in financial services or FinTech
- Strong commercial acumen — ability to build business cases, contribute to P\&L analysis, and drive ROI\-driven product investment decisions
- 3\+ years of direct or indirect external client\-facing experience; comfortable co\-creating and validating products with enterprise clients
- Deep understanding of AI concepts, model risk management, responsible AI frameworks, and enterprise governance requirements
- Exceptional stakeholder management skills and ability to influence without authority in a matrixed global organization
- Background in a relevant financial services domain (Payments, Transaction Banking, Investor Services, or Capital Markets)
- Outstanding verbal and written communication skills across executive, technical, and client audiences
Preferred
- Experience working within or alongside compliance, legal, or risk functions on regulated AI deployments
- Familiarity with Generative AI tools and their practical application to enterprise workflows
- Experience with agile delivery methodologies and cross\-functional product team leadership
Success Measures
- Use case delivery velocity — number of AI products moved from concept to commercialization
- Commercial outcomes — revenue generated and cost savings achieved through AI initiatives
- Client satisfaction and adoption rates for AI\-powered solutions
- Quality and accuracy of business case modelling and ROI tracking
- Strength of internal AI adoption and productivity improvements
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Job Family Group:
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Institutional Sales
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Job Family:
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Corporate Access
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Time Type:
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Full time
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Primary Location:
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New York New York United States
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Primary Location Full Time Salary Range:
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$176,720\.00 \- $265,080\.00
In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental \& vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.
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Most Relevant Skills
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Please see the requirements listed above.
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Other Relevant Skills
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For complementary skills, please see above and/or contact the recruiter.
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Anticipated Posting Close Date:
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Aug 20, 2026
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Automated Processing and AI
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We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision\-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
Illinois residents – AI Notice and Right
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*Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.*
Salary Context
This $176K-$265K range is above the median for AI Product Manager roles in our dataset (median: $185K across 167 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 4,317 AI roles we're tracking, AI Product Manager positions make up 4% of the market. At Citi, 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 in Demand for This Role
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 $217,100 based on 471 positions with disclosed compensation. Disclosed range: $176K to $265K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Citi AI Hiring
Citi has 32 open AI roles right now. They're hiring across AI Product Manager, AI/ML Engineer, AI Agent Developer, AI Software Engineer. Positions span New York, NY, US, Tampa, FL, US, Jacksonville, FL, US. Compensation range: $170K - $300K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 tracked positions.
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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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