Vice President – Generative AI Technical Expert, Data Science & Artificial Intelligence — Hybrid

Citi; New York (NY); On-site; USD 157,000 - 236,000; Full time

Job summary

Citi is seeking a hands-on Generative AI expert to drive development, governance, and delivery of GenAI solutions across banking operations in New York. You will lead technical initiatives with engineers, data scientists, and stakeholders to architect, build, and validate GenAI systems that reduce costs, boost revenue, and enhance customer experience.

Role demands 6+ years in AI/ML within financial services, strong capabilities in LLMs, MLOps, and governance.

Qualifications

• 6+ years in AI/ML, data science, or applied engineering within financial services or a regulated industry.
• Hands-on experience deploying GenAI/LLM solutions in production environments.
• Experience with model risk management, regulatory remediation, and governance processes.
• Familiarity with AI model lifecycles: tuning, evaluation, upgrades.
• Knowledge of core banking data domains and compliance requirements.

Responsibilities

• Design GenAI-powered automation across front, mid, and back-office banking ops.
• Build enterprise GenAI capabilities, including fine-tuning pipelines and semantic layers.
• Own AI solution lifecycle from prototyping to production for high-priority use cases.
• Develop AI tools to accelerate analytics workflows and precision.
• Support model portfolio with tuning, evaluation, and governance artifacts.
• Implement enterprise GenAI infra, guardrails, and regulatory testing frameworks.
• Track model performance, latency, and guardrail effectiveness against benchmarks.

Skills

GenAI

LLMs

RAG

Prompt engineering

MLOps/LLMOps

Python

SQL

Governance & testing

Education

Bachelor’s degree in a quantitative discipline

Master’s degree preferred; Ph.D. a plus

Tools

MLOps/LLMOps

Cloud platforms

Spark

Python

SQL

GitHub/Bitbucket

Job description

About The Role

We are looking for a hands‑on, technically deep Generative AI expert to drive Partner AI Development & Delivery and GenAI Model Governance from an individual‑contributor, technical‑leadership standpoint. This role sits at the intersection of Generative AI innovation, enterprise model governance, and regulatory compliance — building and delivering high‑visibility AI solutions that directly shape business outcomes at scale. You will work as a subject‑matter expert embedded within a broader team, partnering with engineers, data scientists, and stakeholders across Operations, Marketing, Products, Technology, Model Risk, Fair Lending, and Legal. Your focus will be on architecting, building, and validating GenAI solutions, while contributing technical guidance that supports expense reduction, revenue growth, customer experience improvement, compliance transformation, and enterprise GenAI capability buildout.

What You'll Deliver

• Banking Operations AI Automation Design and build GenAI‑powered automation across front, mid, and back office banking operations — including call center IVR, Agent Assist, Collections, and other operational functions. Apply deep technical expertise in LLMs and applied ML, combined with banking domain knowledge, to solve complex, cross‑functional problems at the engineering level.
• Foundation GenAI Capabilities Build and maintain enterprise‑wide foundational GenAI capabilities, including LLM fine‑tuning pipelines and semantic layer development, enabling scalable, data‑driven decision‑making across business functions.
• GenAI Solution Development Take individual technical ownership of the AI solution lifecycle — from prototyping to production — for high‑priority use cases including Personalized Next Best Action decisioning, Campaign Analytics, and Conversational & Contextual Business Insights. Write and review code, design model architectures, and validate performance.
• Analytics Workflow Transformation Build AI‑powered tools and accelerators that improve analytics workflows and productivity. Prototype and evolve AI‑enhanced modeling techniques (e.g., agentic workflows, RAG pipelines) to improve development speed and precision.
• GenAI Model Portfolio Support Provide hands‑on technical support across a GenAI model portfolio — tuning, upgrades, evaluation, and maintenance. Act as a technical contributor to Model Sponsor documentation, providing the technical evidence, testing artifacts, and model documentation required for governance sign‑off under Model Risk Policy.
• Enterprise GenAI Capabilities Build and implement firm‑wide GenAI technical infrastructure: adversarial testing harnesses, regulatory testing frameworks, guardrails, and near real‑time monitoring pipelines. Contribute technical input into AI governance policy development alongside the second line of defense.
• Measurable Technical Delivery Track and report technical delivery outcomes (model performance, latency, accuracy, guardrail effectiveness) against defined engineering and business benchmarks.

How You'll Deliver

Apply Deep Technical Expertise Bring hands‑on proficiency in GenAI/LLM engineering to solve enterprise‑grade problems, staying current with emerging techniques (agentic AI, RAG, fine‑tuning, prompt engineering) and applying them pragmatically to production systems.

Collaborate with Central AI and Business Teams Work as a technical partner with the firm's Central AI organization and business units, contributing architecture recommendations and technical designs that support process redesign and measurable change.

Contribute to Prioritization Discussions Provide technical feasibility assessments and effort estimates to business stakeholders and analytics leadership to support prioritization of high‑impact AI solutions.

Uphold a Strong Controls Mindset Apply and follow control processes across Information Security, Platform Security, and Data Security in all technical work, ensuring GenAI solutions are built and deployed securely and compliantly.

Experience

• 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 — sufficient to translate business requirements into technical solutions
• 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

Technical Skills

• GenAI & ML: Generative AI, LLMs, RAG, Agentic AI, prompt engineering, LLM fine‑tuning, NLP, supervised/unsupervised learning, mathematical optimization & decision science
• Engineering & Infrastructure: MLOps/LLMOps, cloud‑native AI platforms, big data, distributed computing, Spark, Python, SQL — strong hands‑on coding ability expected
• Governance & Testing: Building adversarial testing suites, guardrails, regulatory testing frameworks, and near real‑time model monitoring solutions
• Tooling: SDLC, version control (Bitbucket/GitHub), JIRA, CI/CD and DevOps practices
• Regulatory Awareness: Working knowledge of SR 11‑7, SR 26‑2, OCC AI guidance, CFPB, Fair Lending, ECOA as they apply to AI/ML deployment within a regulated institution

Communication & Collaboration

• Ability to work effectively as an embedded technical expert within cross‑functional, matrixed teams
• Strong stakeholder communication skills — able to explain technical concepts, trade‑offs, and model behavior clearly to non‑technical partners
• Solid documentation and technical writing skills to support model governance and audit requirements
• Comfortable presenting technical findings and demos to mid‑to‑senior audiences

Education

• Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Engineering, or Economics) required
• Master's degree preferred; Ph.D. a plus

Job Family Group

Decision Management

Job Family

Specialized Analytics (Data Science/Computational Statistics)

Time Type

Full time

Primary Location

New York New York United States

Primary Location Full Time Salary Range

$157,040.00 - $235,560.00

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.

Anticipated Posting Close Date: Sep 25, 2026

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.

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