Lead AI and Machine Learning Engineer - Vice President OR Lead AI Engineer, Generative AI - Vice President

Job Description We’re currently looking for a high caliber professional to join our team as Vice President, Application Development Tech Lead Analyst (C13) based in Pune, India. XVA Technology at Citi is undertaking a bold, multi-year transformation to build a best-in-class centralized cross asset platform risk system. We are re-engineering our technology estate to achieve world-leading performance and resiliency, enabling new capabilities. Our ambition is to deliver a seamlessly integrated, highly automated platform that drives outstanding client outcomes and accelerates growth across our global franchise. As part of the team, you'll collaborate closely with high-caliber engineers and deeply engaged business and product partners - working together to define and deliver the next generation of XVA technology at Citi. Role Overview/What will you do: As an Applications Development Technology Lead Analyst, you will be instrumental in shaping the future of our product quality and delivery, working towards a target state of a fully automated platform with minimal manual QA intervention. This role specifically requires deep expertise in agentic AI and extensive hands-on experience in Generative AI (GenAI) projects. While a solid foundation in Machine Learning (ML) is beneficial, the successful candidate will be instrumental in architecting and implementing scalable AI frameworks, translating complex ideas into robust, production-ready systems, and contributing to Citi's strategic AI initiatives. Key Responsibilities: GenAI Solution Development: Hands-on implementation, and deployment of scalable, robust agentic AI frameworks and Generative AI solutions for critical banking use cases, ensuring high performance, reliability, and security. Full-Stack Application Integration: Build full-stack applications that seamlessly integrate state-of-the-art Machine Learning (ML) and Large Language Model (LLM) tools and services into comprehensive AI solutions. AI Advancement & Prototyping: Proactively explore, prototype (Proof of Concept), and integrate the latest advancements in AI, particularly in agent-based systems, autonomous AI, and generative AI technologies. Collaboration: Fostering collaboration with cross-functional teams including AI researchers, data scientists, product managers, and software engineers to integrate and scale AI solutions across Citi’s products and services. Code Development & Standards: Write high-quality production code, drive proof-of-concepts, and validate architectural decisions through implementation. Set technical standards, guide design choices, and raise the bar for the team. Deployment: Take AI-enabled capabilities from early exploration and proof-of-concept through to secure, reliable, and production deployments, focusing on cloud-native, container-first services built to scale for enterprise use. Performance Evaluation: Design and implement rigorous metrics and evaluation strategies for AI system and agent performance, driving continuous optimization and behavioral improvement.

Experience: 12 to 15 years of deep hands-on experience in engineering and executing scalable enterprise solutions. AI Expertise: Deep expertise in AI principles, agent-based systems, machine learning, and advanced software engineering practices. Programming Proficiency: Expert proficiency in Python programming language is essential. GenAI Frameworks: Proven experience in implementing Generative AI use cases using frameworks like LangChain, AutoGen, CrewAI. LLM Implementation: Advanced knowledge in Large Language Models (LLM), with hands-on experience in implementing LLMs using vector databases and Retrieval-Augmented Generation (RAG), as well as tuning models. Ability to perform solution architecture validations for LLMs. ML & NLP: Understanding of machine learning models, experience with Natural Language Processing (NLP) libraries and tools. GenAIOps: Experience in putting Generative AI (GenAI) models into production and providing support to them (GenAIOps). MLOps: Experience using MLOps tools like MLflow for lifecycle management of machine learning models. Containerization: Experience in using Docker to create reproducible and scalable environments. Problem-Solving: Strong analytical and problem-solving skills with an aptitude for math and statistics. Communication: Excellent communication and collaboration skills, with the ability to engage effectively with diverse stakeholders. Self-Motivation: Self-motivated and capable of working independently as well as part of a team in a fast-paced environment. Business knowledge of CVA, XVA, regulatory stress testing is preferred Education: • Bachelor’s in Computer Science, Mathematics or equivalent. • A Master’s degree in preferred ------------------------------------------------------ Job Family Group: Technology------------------------------------------------------ Job Family: Applications Development------------------------------------------------------ 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.