Lead AI Engineer, Senior Vice President

Discover your future at Citi -------------------------------- Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you’ll have the opportunity to grow your career, give back to your community and make a real impact. Job Overview ---------------- We are building the most consequential AI solutions in Funds Transfer Pricing and Financial Hedging platforms, and we are seeking a Lead AI Engineer to own the technical vision and drive the execution for these domains. In this position, you will be accountable for the end-to-end technical success of our agentic solutions, from architectural vision and design through implementation and adoption, ensuring they deliver scalable, resilient, and business-impacting capabilities at global scale. Responsibilities: Strategy \& Technical Ownership * Define and own the end-to-end technical strategy for agentic AI within the Funds Transfer Pricing and Financial Hedging domains, ensuring alignment with both business objectives and the firm's technology standards. * Serve as the ultimate technical authority on agentic systems, providing expert guidance to senior leadership and translating complex business challenges into a clear, actionable technical roadmap. * Lead by example through hands-on coding, personally architecting and contributing to the most critical and complex components of the system, setting the standard for code quality and innovation. * Mentor and cultivate a team of senior AI engineers, fostering a culture of technical excellence, continuous learning, and collaborative problem-solving. System Architecture \& Design * Own the architectural vision for highly scalable, resilient, and performant multi-agent systems, establishing the blueprint and design patterns that will be used across the platform. * Oversee the design of intelligent agentic systems, including reasoning, planning, memory, orchestration, and action execution, ensuring they are scalable, reliable, auditable, and fit for business-critical workflows Development Guidance \& Implementation * Guide the team in implementing robust AI agents while personally driving the development of core components and complex features. * Set the strategy for integrating advanced technologies, including large language models (LLMs), predictive models, and sophisticated reasoning frameworks, to continuously expand agent capabilities. * Establish and enforce best practices for designing and optimizing Retrieval-Augmented Generation (RAG) architectures and vector data strategies. Quality, Performance \& Governance * Own the comprehensive strategy for AI system quality, defining the frameworks and metrics for measuring and optimizing agent performance, reliability, and task success. * Establish and enforce rigorous standards for AI governance, explainability (XAI), and responsible AI, ensuring systems are transparent, auditable, and compliant. Required Qualifications \& Skills * Extensive professional experience in software development and system design, with at least 5 years in a technical leadership capacity, guiding senior engineering teams in delivering large-scale, complex systems. * Architectural Mastery of the AI Ecosystem: A proven track record of architecting solutions with the modern AI ecosystem. This requires deep, hands-on expertise with frameworks for agent development (Google ADK), multi-agent orchestration (LangGraph, AutoGen, CrewAI), and data augmentation (LangChain, LlamaIndex). * Proven Expertise in Agentic Systems: A track record of architecting and delivering complex single- and multi-agent systems, demonstrating expertise in planning/reasoning engines, memory systems, and agentic protocols like MCP. * Deep, Practical Knowledge of LLMs: Demonstrated mastery of LLM fundamentals, Prompt Engineering, and Context Engineering, with a history of applying this knowledge to build sophisticated agentic architectures and design robust APIs for AI services. * Deep expertise in enterprise Retrieval-Augmented Generation (RAG) architectures, including document ingestion, embedding strategies, retrieval optimization, reranking, vector databases, and context management. * Expert-Level Engineering Craftsmanship: Expert-level proficiency in Python and SQL applied to building production-quality, high-performance AI systems. * Proven ability to lead technical strategy, influence senior stakeholders, drive architecture decisions across multiple teams, and mentor senior engineers and technical leads. Beneficial Qualifications \& Skills * Experience working in the financial services industry. * Proficiency in Java as an additional programming language. Education * Bachelor’s degree/University degree in Computer Science * Master's degree 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.*