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Vice President – Generative AI Technical Expert, Data Science & Artificial Intelligence
Citi. Drive Partner AI Development & Delivery and GenAI Model Governance from an individual-contributor, technical-leadership standpoint .
Posted 9/18/2026full-timeNew York City • New York • United StatesLead💰 $157,040 - $235,560 per yearWebsite
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Generative AI solution architecture, model governance, and AI lifecycle management within regulated financial services. Proficient in building and deploying AI/ML models, ensuring compliance with model risk management and regulatory standards.
Highest-signal resume keywords
Generative AI Solution DevelopmentModel Risk ManagementAI/ML Model Lifecycle ManagementPython ProgrammingCloud-Native AI Platforms
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Generative AILLMsRAGNLPSupervised LearningUnsupervised LearningMathematical OptimizationDecision ScienceMLOpsSQL
Soft Skills
Stakeholder CommunicationTechnical WritingPresentation SkillsCross-Functional Collaboration
Tools & Technologies
SparkBitbucketGitHubJIRACI/CDDevOps Practices
Industry Keywords
Financial ServicesModel Risk ManagementFair LendingComplianceCredit Card Economics
Tech Stack
Tools & technologiesCloudPythonSDLCSparkSQL
About the role
Key responsibilities & impact- Drive Partner AI Development & Delivery and GenAI Model Governance from an individual-contributor, technical-leadership standpoint
- Architect, build, and validate Generative AI solutions for enterprise use
- Design and build GenAI-powered automation across front, mid, and back office banking operations, including call center IVR, Agent Assist, and Collections
- Build and maintain enterprise-wide foundational GenAI capabilities, including LLM fine-tuning pipelines and semantic layer development
- Take technical ownership of AI solution lifecycles from prototyping to production for Personalized Next Best Action decisioning, Campaign Analytics, and Conversational & Contextual Business Insights
- Write and review code, design model architectures, and validate performance
- Build AI-powered tools and accelerators to improve analytics workflows and productivity
- Prototype and evolve AI-enhanced modeling techniques, including agentic workflows and RAG pipelines
- Support GenAI model portfolio tuning, upgrades, evaluation, and maintenance
- Provide technical evidence, testing artifacts, and model documentation for governance sign-off under Model Risk Policy
- Build and implement adversarial testing harnesses, regulatory testing frameworks, guardrails, and near real-time monitoring pipelines
- Contribute to AI governance policy development alongside the second line of defense
- Track and report technical delivery outcomes against engineering and business benchmarks
- Partner with Central AI, business units, engineers, data scientists, and stakeholders across Operations, Marketing, Products, Technology, Model Risk, Fair Lending, and Legal
- Provide technical feasibility assessments, effort estimates, architecture recommendations, and technical designs
- Apply Information Security, Platform Security, and Data Security controls to technical work
Requirements
What you’ll need- 6+ years in AI/ML, data science, or applied engineering roles within financial services or a similarly regulated industry
- Demonstrated hands-on experience building and deploying Generative AI/LLM solutions in production environments
- Practical experience supporting model risk management, regulatory remediation, and model documentation/governance processes
- Experience working with AI/ML model lifecycles, including tuning, evaluation, and upgrades
- Working knowledge of core banking data domains — marketing, customer management, call center operations, collections, complaints, and financial controls
- Familiarity with credit card economics, customer behavior, and product strategy as they relate to data/AI use cases
- Exposure to Model Risk Management, Fair Lending, and Compliance requirements in a regulated financial institution
- Generative AI, LLMs, RAG, Agentic AI, prompt engineering, LLM fine-tuning, NLP, supervised/unsupervised learning, mathematical optimization, and decision science
- MLOps/LLMOps, cloud-native AI platforms, big data, distributed computing, Spark, Python, and SQL; strong hands-on coding ability
- Building adversarial testing suites, guardrails, regulatory testing frameworks, and near real-time model monitoring solutions
- SDLC, version control (Bitbucket/GitHub), JIRA, CI/CD, and DevOps practices
- Working knowledge of SR 11-7, SR 26-2, OCC AI guidance, CFPB, Fair Lending, and ECOA
- Ability to work effectively within cross-functional, matrixed teams
- Strong stakeholder communication skills
- Solid documentation and technical writing skills
- Comfortable presenting technical findings and demos to mid-to-senior audiences
- Bachelor's degree in a quantitative discipline required
- Master's degree preferred; Ph.D. a plus
Benefits
Comp & perks- Discretionary and formulaic incentive and retention awards
- Medical, dental & vision coverage
- 401(k)
- Life, accident, and disability insurance
- Wellness programs
- Planned time off (vacation)
- Unplanned time off (sick leave)
- Paid holidays