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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 more than 230,000 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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Citi is establishing a new, unified firmwide AI organization under a newly created Group Head of Artificial Intelligence \- merging the firm's Head of AI and CTO responsibilities into a single executive accountable for AI\-led transformation across every business and function. This post\-merger structure is intentionally distinct from prior models and will be the engine through which Citi competes in the AI era.
The Head of AI\-First Development is the leader who re\-architects how Citi builds products. The mandate is to make AI the default across the firm's entire Product Development Lifecycle \- from requirements through code, test, and deployment. This is a rare Managing Director level mandate to lead one of the largest engineering productivity transformations in global financial services.
Why This Role
You will redefine what it means to build products. The platform you build and the workflows you establish will shape how all of Citi’s businesses ship products and will be one of the largest, most visible bets the firm makes on the productivity of its own people. Few seats in financial services offer a comparable canvas for an engineering leader.
Key Responsibilities
AI\-First PDLC
- Re\-architect Citi's end\-to\-end Product Development Lifecycle (PDLC) so that AI is the default \- across requirements gathering, design, code, test, deployment, and operations.
- Define and own the firm's reference workflows, standards, and patterns for AI\-first product development; partner with the broader Tech and Product organizations to drive consistent adoption.
- Continuously evolve the PDLC as the underlying AI tooling, models, and developer practices mature.
Agentic Developer\-Experience Platform
- Own the agentic product development platform including agentic requirements tools, testing tools, coding tools, AI\-assisted code review, automated testing, and deployment agents.
- Define the firm's "build vs. buy vs. partner" strategy for developer AI tooling; manage the relationships with the agentic coding vendors and platform providers that matter most.
- Establish the engineering productivity metrics, telemetry, and feedback loops that Leadership, Governance \& Reporting
What Success Looks Like (First 12 Months)
- A defined, adopted AI\-first PDLC reference workflow, with named pilot organizations operating end\-to\-end against it.
- A consolidated, supported end to end agentic development platform live for a meaningful adoption, with credible telemetry on usage and productivity.
- A trusted, transparent engineering productivity scorecard accepted by Tech leadership and the CFO.
- A visible shift in product development culture toward AI\-first as the default.
Qualifications
- 15\+ years of progressive engineering leadership experience, including senior roles owning developer experience, developer platforms, or engineering productivity at scale \- ideally inside an elite engineering culture (top\-tier tech firm, hyperscaler, or major bank with a serious engineering bar).
- Seasoned DevEx / developer\-platform leader \- has personally built and run a developer platform serving thousands (ideally tens of thousands) of engineers, with demonstrable productivity outcomes.
- Deep, current expertise in agentic coding tools and the AI\-first SDLC \- fluent in the modern landscape (agentic IDEs, code\-generation models, AI\-assisted review and test, deployment agents) and the operational realities of running them at enterprise scale.
- Influential change agent \- proven ability to win over skeptical users and engineers; leads through credibility and outcomes, not mandate.
- Strong product instinct \- runs the platform as a true product, with clear users, telemetry, prioritization, and outcome accountability.
- Strong appreciation of Cyber security and Architectural standardization concerns, to work in partnership with the CISO and CTO teams.
- Cross\-functional influencer \- proven ability to operate in a matrixed environment across platform, controls, HR, and the broader Tech organization without direct authority over all of them.
- Risk \& Compliance awareness – understands and fully appreciates risks, controls, and regulatory expectations as they apply to AI\-assisted development in global banking.
- Excellent communication \- credible with engineers, engineering leaders, business stakeholders, controls partners, and regulators alike.
- Financial Services fluency preferred; comparable experience in another regulated, large\-scale engineering environment will be considered.
Education
- Bachelor's degree required, preferably in Computer Science, Engineering, or a related technical discipline.
- Advanced technical degree or MBA preferred.
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Job Family Group:
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Technology
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Job Family:
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Applications Development
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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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$250,000\.00 \- $500,000\.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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*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 $250K-$500K range is above the 75th percentile 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 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 $213,800 based on 583 positions with disclosed compensation. Director-level AI roles across all categories have a median of $247,800. This role's midpoint ($375K) sits 75% above the category median. Disclosed range: $250K to $500K.
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.
Citi AI Hiring
Citi has 17 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist, AI Software Engineer, AI Product Manager. Positions span New York, NY, US, Jacksonville, FL, US, Jersey City, NJ, US. Compensation range: $106K - $500K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% 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.
Frequently Asked Questions
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