About the Role
We are looking for a Senior Gen AI Engineering leader to design and build AI/ML solutions that power intelligent digital experiences across customer-facing and operational platforms. This role requires deep expertise in AI/ML, including LLM-powered workflows, agentic AI systems, and machine learning models, to enable natural language understanding, intelligent automation, and personalized self-service at scale.
As a Vice President, you will lead a team with full responsibility for people, budget, and performance, while connecting intelligent AI systems with enterprise platforms across millions of multilingual customer interactions.
If you are passionate about building production-grade AI using LLMs, RAG, and Agentic AI and thrive on growing high-performing teams, this role is for you.
Key Responsibilities
Generative AI & Agentic AI
- Lead the design and development of scalable, enterprise-grade conversational AI and agentic systems for real-time customer interaction use cases
- Build and optimize AI/ML solutions including LLM-powered workflows using GPT, Claude, Gemini, or equivalent models
- Design and deploy multi-agent systems to automate complex customer journeys and business workflows
- Apply advanced prompt engineering, evaluation frameworks, and guardrails to improve AI response quality, cost, and accuracy
RAG & Knowledge Systems
- Develop and implement RAG pipelines and knowledge-based AI integrations
- Integrate vector databases and enterprise knowledge repositories
- Improve retrieval accuracy, response relevance, and grounding of AI-generated content
Software Engineering
- Build scalable backend services and APIs using Java and/or Python.
- Develop cloud-native microservices and integrate AI capabilities into customer-facing applications.
- Collaborate with architects, product managers, and business stakeholders to deliver high-impact solutions.
AI Operations & Governance
- Monitor model performance, latency, and operational costs.
- Implement AI governance, observability, and responsible AI practices.
- Optimize LLM usage and inference costs in production environments.
Required Skills & Experience
Must Have
- 11–16 years of experience in application development or enterprise engineering roles
- Expert-level proficiency in Python (mandatory)
- Strong hands-on expertise in Java, Microservices, and REST APIs
- 2+ years of hands-on experience with AI/ML and LLMs (e.g., GPT, Claude, Gemini)
- Experience with RAG, prompt engineering, and vector databases
- Experience with agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI)
- Strong understanding of system design, distributed systems, and cloud platforms
- Full-stack development experience with modern frontend frameworks (e.g., React.js / Angular)
- Experience with SQL/NoSQL databases and real-time data processing
Nice to Have
- MLOps experience (deployment, monitoring, model lifecycle management)
- Experience with recommendation engines or conversational AI platforms
- Knowledge of financial services, wealth management, or digital banking
- Experience with AI governance and responsible AI practices
What Success Looks Like
- Build AI-powered experiences at scale for millions of customers
- Deliver production-ready GenAI and Agentic AI solutions
- Drive customer engagement and operational efficiency through AI
- Lead high-performing teams to adopt and deliver emerging AI technologies
Good to Have
- Experience in Financial Services / Banking domain
- Exposure to recommendation systems, personalization, or conversational AI
- Knowledge of customer journey analytics, sentiment analysis, or automation workflows
- Experience working in product-based or large-scale enterprise environments
Role Type
- Individual Contributor (Hands-on)
- High ownership role with cross-functional collaboration
What We’re Looking For
- Strong technologist with the ability to bridge traditional engineering and AI
- Hands-on problem solver with a product mindset
- Ability to work in a fast-evolving AI landscape and drive innovation
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Job Family Group: Technology------------------------------------------------------
Job Family:Digital Software Engineering------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
Skills Required
- 11 - 16 years of experience in application development or enterprise engineering roles
- Strong hands-on expertise in Java, Microservices, and REST APIs
- Expert-level proficiency in Python
- 2+ years of hands-on experience with AI/ML, LLMs (e.g., GPT, Claude, Gemini)
- Experience with RAG, prompt engineering, and vector databases
- Familiarity with agentic AI frameworks (e.g., LangChain, LangGraph, CrewAI)
- Full-stack development experience with modern frontend frameworks (e.g., React.js/Angular)
- Strong understanding of system design, distributed systems, and cloud platforms
- Experience with SQL/NoSQL databases and real-time data processing
- Exposure to MLOps practices including deployment, monitoring, and lifecycle management
Citi Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.
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Healthcare Strength — Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
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Retirement Support — Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
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Wellbeing & Lifestyle Benefits — Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.
Citi Insights
What We Do
Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.
