Overview of the Role:

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 Enterprise 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.

We are seeking a highly skilled and experienced Senior AI/ML & Agentic AI Engineer with a robust background in Python, Java, database technologies, cloud platforms, and CI/CD DevOps practices to join our Engineering Excellence and Transformation organization. In this critical role, you will be at the forefront of designing, developing, and integrating cutting-edge AI/ML and Agentic AI solutions, including advanced AI assistant tools, to revolutionize engineering processes and drive significant operational improvements across our enterprise. You will leverage your comprehensive technical expertise to build scalable, resilient, and high-performance AI systems from conception to deployment, fostering a culture of innovation and continuous delivery.

Key Responsibilities:

• Lead the design, development, and implementation of sophisticated AI/ML, Generative AI, and Agentic AI solutions, including AI assistant tools, in close collaboration with AI architects, product owners, and cross-functional engineering teams within the Engineering Excellence framework.

• Architect and develop end-to-end AI systems, leveraging both Python for machine learning workflows and Java for scalable enterprise-grade backend services, ensuring seamless integration with existing and new applications.

• Design and implement intelligent agentic systems that exhibit autonomous decision-making capabilities, enabling advanced automation and self-optimizing processes.

• Develop, fine-tune, and optimize Large Language Models (LLMs) using both parameter-efficient techniques and full fine-tuning, focusing on their integration into robust, production-ready systems supported by both Python and Java components.

• Drive the implementation and experimentation with advanced generative AI methods such as prompt engineering and Retrieval-Augmented Generation (RAG), ensuring their effective deployment and performance in enterprise environments.

• Own the deployment pipeline for AI models and associated services, leveraging CI/CD methodologies, containerization (Docker), and orchestration (Kubernetes) on leading cloud platforms (AWS, Azure, GCP) to ensure secure, scalable, and automated releases.

• Apply deep knowledge of database technologies (SQL and NoSQL) to design efficient data storage, retrieval, and management strategies for AI applications, ensuring data integrity and performance.

• Contribute to the establishment and enforcement of engineering best practices, architectural patterns, and tooling standards for full-stack AI development, advocating for maintainability, observability, and cost-efficiency.

• Stay abreast of the latest advancemen