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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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About Citi:
Citi, the leading global bank, has approximately 200 million customer accounts and does business in more than 160 countries and jurisdictions. Citi provides consumers, corporations, governments, and institutions with a broad range of financial products and services, including consumer banking and credit, corporate and investment banking, securities brokerage, transaction services, and wealth management.
As a bank with a brain and a soul, Citi creates economic value that is systemically responsible and in our clients’ best interests. As a financial institution that touches every region of the world and every sector that shapes your daily life, our Operations \& Technology teams are charged with a mission that rivals any large tech company. Our technology solutions are the foundations of everything we do from keeping the bank safe, managing global resources, and providing the technical tools our workers need to be successful to designing our digital architecture and ensuring our platforms provide a first\-class customer experience. We reimagine client and partner experiences to deliver excellence through secure, reliable, and efficient services.
Our commitment to diversity includes a workforce that represents the clients we serve from all walks of life, backgrounds, and origins. We foster an environment where the best people want to work. We value and demand respect for others, promote individuals based on merit, and ensure opportunities for personal development are widely available to all. Ideal candidates are innovators with well\-rounded backgrounds who bring their authentic selves to work and complement our culture of delivering results with pride. If you are a problem solver who seeks passion in your work, come join us. We’ll enable growth and progress together.
The Role:
Citi is seeking a seasoned Cybersecurity Product Manager (AI \& Security Ops)to own the end\-to\-end product management and enterprise delivery of major security operations platforms across a complex, multi\-stakeholder environment. This is a senior\-level, high\-impact role requiring a rare and deliberate combination of hands\-on cybersecurity operations experience, enterprise product management discipline, vendor governance expertise, and applied fluency in Artificial Intelligence (AI) as it relates to security operations. The successful candidate will apply that practitioner credibility to translate competing stakeholder needs into structured roadmaps, user stories, and platform/product delivery outcomes. They will serve as the authoritative customer voice for the assigned products while holding vendors to rigorous contractual and performance standards. This role sits at the intersection of cybersecurity operations, security engineering, and responsible AI enablement, and is central to the future of Citi's security operations capabilities.
The Ideal Candidate:
The ideal candidate has spent meaningful time on the operational front lines of cybersecurity operations and has subsequently moved into product or program management roles where they translate that practitioner knowledge into platform strategy and delivery. They have run or held an authoritative position in engineering and SDLC processes, running agile/scrum teams. They understand the needs of both operations and engineering and have proven experience managing vendors to ensure those needs are met.
Critically, the ideal candidate approaches product capabilities, particularly leveraging AI, with informed skepticism and strategic clarity. They understand that AI can meaningfully accelerate detection, triage, and response, but also that a poorly validated model can generate alert fatigue, erode analyst trust, and introduce new risks. They can distinguish genuine capabilities from vendor marketing, ask the right questions about security capabilities and ensure that AI\-driven features empower operational teams rather than undermine them. They bring both credibility with operational teams and the organizational influence to drive a complex, multi\-stakeholder product agenda that responsibly integrates AI into the future of security operations.
Responsibilities
- Own and drive the end\-to\-end product roadmap for one or more major security operations platforms, balancing requirements from 10\+ distinct internal customer groups including SOC, Threat Intelligence, Incident Response, Insider Threat, Vulnerability Management, IT Risk, Legal, Compliance, and Business units.
- Develop and maintain a clearly prioritized product backlog, facilitate structured intake and prioritization processes, and define and track product OKRs, KPIs, and success metrics — including AI\-specific performance indicators such as detection accuracy, false positive rates, and model drift.
- Apply first\-hand cybersecurity operations expertise to translate analyst needs into high\-quality product artifacts including user stories, user journeys, acceptance criteria, and functional specifications — including workflows augmented by AI\-assisted tooling.
- Identify, document, and translate AI use cases into actionable product requirements, addressing operational pain points such as alert triage automation, anomaly detection, natural language threat querying, and AI\-assisted investigation.
- Evaluate vendor\-provided capabilities critically, assessing maturity, suitability, and growth potential. Require documented evidence of model validation, performance benchmarks, and drift management processes.
- Serve as the primary product\-level point of accountability for vendor relationships, leading governance forums, quarterly business reviews (QBRs), and escalation proceedings while enforcing SLA compliance and contractual obligations.
- Collaborate with Citi's AI/ML, Data Science, and Enterprise AI Governance teams to ensure AI features embedded in Security Operations products comply with internal policies, model risk management requirements, and applicable regulatory guidance.
- Serve as Product Owner in Agile/Scrum ceremonies across one or more concurrent delivery workstreams, partnering with program managers, development teams, and platform architects to deliver roadmap initiatives on schedule and within scope.
- Coordinate user acceptance testing (UAT) across multiple customer groups, ensuring quality gates and AI feature output benchmarks are met prior to production releases.
- Drive platform adoption across customer groups through structured change management, onboarding guides, and enablement sessions. Champion practitioner\-centered design and appropriate human oversight of AI\-driven workflows in all product decisions.
- Present platform health, roadmap status, and AI feature performance to senior cybersecurity leadership and technology executives on a recurring cadence.
Qualifications
- 6\+ years' combined professional experience across all four of the following domains, with demonstrated experience in each: enterprise product and project management with roadmap ownership and vendor accountability; cybersecurity engineering with hands\-on platform design or integration; cybersecurity operations including SOC analysis, incident response, threat hunting, or insider threat investigation; and AI enablement from concept through deployment.
- Demonstrated working knowledge of AI and machine learning concepts applied to cybersecurity, including behavioral analytics, anomaly detection, LLM\-based security tooling, and SOAR or agentic AI automation.
- Proven ability to critically evaluate vendor AI product claims, enforce appropriate testing and acceptance standards, and manage escalation and contractual accountability.
- Demonstrated expertise translating operational and technical cybersecurity requirements into structured product artifacts including user stories, user journeys, acceptance criteria, and multi\-quarter roadmaps.
- Strong executive communication skills, written and verbal, with the ability to present complex technical, AI, and product topics clearly to senior leadership and non\-technical stakeholders.
- Experience functioning as a Product Owner or equivalent role on Agile/Scrum delivery teams.
- Experience evaluating or deploying AI\-native security products including AI\-powered SIEM, SOAR, UEBA, NDR, or EDR platforms, or LLM\-based security tooling.
- Familiarity with AI governance frameworks (NIST AI RMF, SR 11\-7\), cybersecurity frameworks (NIST CSF, MITRE ATT\&CK), and experience in regulated environments subject to SOX, FFIEC, OCC, or GDPR is preferred.
- Experience at a major financial institution or equivalent regulated enterprise is preferred.
Education
- Bachelor's degree in Computer Science, Information Systems, Cybersecurity, Engineering, Business Administration, related field or equivalent experience.
- Master's degree preferred.
- Product management certifications such as PMP, SAFe POPM, or CSPO are preferred.
- Security certifications such as CISSP, CISM, or GIAC (GCIA, GCIH, GDAT) are preferred.
This job description provides a high\-level review of the types of work performed. Other job\-related duties may be assigned as required.
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Job Family Group:
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Technology
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Job Family:
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Information Security
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Time Type:
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Full time
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Primary Location:
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Irving Texas United States
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Primary Location Full Time Salary Range:
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$125,760\.00 \- $188,640\.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 18, 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 $125K-$188K range is in the lower quartile 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. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($157K) sits 28% below the category median. Disclosed range: $125K to $188K.
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
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 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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