Lead AI Engineer, Senior Vice President in London

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 (Lang Graph, Auto Gen, Crew AI), and data augmentation (Lang Chain, Llama Index).

• 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
• Time Type
• Full time

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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