Lead Python AI Engineer, Agentic Systems

Responsibilities

• Design and build multi-agent systems where autonomous agents collaborate to solve complex, real-world business problems across financial platforms.
• Develop and optimize Retrieval-Augmented Generation (RAG) architectures, including embedding strategies, vector databases, and retrieval pipelines, to improve the accuracy and reliability of AI-generated outputs.
• Implement planning and reasoning capabilities using knowledge graphs, rule-based reasoning, and search algorithms that enable agents to execute multi-step workflows reliably.
• Construct resilient agent architectures with built-in mechanisms for error recovery, self-correction, and feedback-driven improvement to maintain performance in production environments.
• Integrate large language models (LLMs), predictive models, and reasoning frameworks into agent systems that support complex financial decision-making workflows.
• Build APIs, tools, and microservices that connect AI capabilities with enterprise applications, enabling seamless integration at scale.
• Optimize AI systems for low latency and high throughput, applying techniques such as response streaming, caching, and token usage optimization to ensure performance and cost-effectiveness.
• Apply current AI research to real business challenges and collaborate with engineers across the team to elevate AI development practices and foster engineering excellence.
• Act as a subject matter expert, driving the technical strategy for AI within the Funds Transfer Pricing and Financial Hedging domains by staying abreast of state-of-the-art research and identifying opportunities for innovation.
• Mentor junior engineers on AI best practices and provide technical leadership across multiple project teams, fostering a culture of engineering excellence.

Requirements

• 7 or more years of professional experience in software development and system design, with a demonstrated history of delivering large-scale production systems.
• Proficiency in Python and SQL, with hands-on experience building production-quality Agentic AI solutions using frameworks such as LangChain, LlamaIndex, or equivalent tools.
• PRACTICAL experience developing multi-agent systems using frameworks such as Google ADK, LangGraph, AutoGen, or CrewAI, including implementation of planning, reasoning, and memory systems.
• APPLIED knowledge of large language models (LLMs) within agentic architectures, including designing and integrating APIs for AI services.
• Advanced skills in Prompt and Context Engineering, with the ability to structure, compress, and optimize information for consistent and high-quality model performance.
• Experience working with Vector Databases as part of AI retrieval and memory architectures.

Qualifications

• Master's degree in Computer Science or a closely related field.
• Experience working within the financial services industry, particularly in areas such as Funds Transfer, Pricing, Hedging, or Treasury technology.
• Proficiency in Java as a secondary programming language alongside Python.

Benefits

At Citi, you will work alongside talented engineers on technology that operates at global scale and drives real impact across financial markets. This is a high-visibility role within a firm-wide AI modernization initiative, offering the technical scope and career momentum that comes with building systems that matter.

The opportunity to work on a firm-wide AI initiative with broad organizational impact, giving your work visibility at the highest levels of the business.

Access to continuous learning and professional development, with exposure to cutting-edge AI research and the tools to apply it in production.

Collaboration with a high-caliber engineering team where knowledge sharing, mentorship, and technical growth are part of how the team operates every day.

Competitive compensation and a comprehensive benefits package that supports your financial wellbeing and long-term security.

Wellbeing and family support programs designed to help you maintain balance across all areas of life.

The scale and reach of a global institution, with the ability to see the direct effect of your engineering work across international markets and platforms.