Lead Python AI Engineer, Agentic Systems

CitiIrving, TX
$125,760 - $188,640Hybrid

About The Position

Citi is building some of the most consequential AI solutions in global financial services, and this Senior AI Engineer role sits at the heart of that mission — designing and developing production-grade Agentic AI systems for Funds Transfer Pricing and Financial Hedging platforms. You will take ownership of complex AI agent architectures from concept through to global-scale deployment, driving automation and decision intelligence across critical financial workflows. This is an opportunity to shape the next generation of AI-powered financial technology at one of the world's leading institutions.

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.

Nice To Haves

  • 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.
  • A Master's degree in Computer Science or a closely related field.

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

Benefits

  • medical
  • dental & vision coverage
  • 401(k)
  • life, accident, and disability insurance
  • wellness programs
  • paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays
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