Lead Python AI Engineer, Agentic Systems

Citi

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Irving, TX
Salary
$125,760–$188,640 / yr
Posted
17 days ago
Freshness
Confirmed live yesterday
Closes
Sep 30, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $212k
This role $157k
$110k most similar roles pay here $276k

This role pays less than 87% of similar roles. Most pay $177,187–$246,150 — the shaded band above. At the midpoint, this role pays about $157k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About Citi

Citi is one of the world’s most trusted financial institutions, proudly serving millions of customers across the United States.

Citi currently has 256 open roles on FindRole.

Listed pay typically runs $140,080–$210,120 across 238 roles with salary data.

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At a glance

TL;DR · Lead Python AI Engineer, Agentic Systems

Lead Python AI Engineer, Agentic Systems joins the Agentic AI engineering team to design and develop production-grade Agentic AI systems for Funds Transfer Pricing and Financial Hedging platforms. This role involves building multi-agent systems where autonomous agents collaborate to solve complex business problems, optimizing Retrieval-Augmented Generation (RAG) architectures, and implementing planning and reasoning capabilities using knowledge graphs and search algorithms. The engineer will construct resilient architectures with error recovery, integrate large language models and predictive models into decision-making workflows, and build APIs and microservices for enterprise integration. Key technologies include Python, SQL, LangChain, LlamaIndex, Google ADK, LangGraph, AutoGen, or CrewAI. Candidates must possess expertise in Prompt and Context Engineering, vector databases, and potentially Java. The role addresses the technical challenge of automating complex financial workflows through advanced AI-driven decision intelligence.

What you'll do

  • Design and build multi-agent systems where autonomous agents collaborate to solve complex financial business problems.
  • Develop and optimize Retrieval-Augmented Generation (RAG) architectures, including embedding strategies and vector databases.
  • Implement planning and reasoning capabilities using knowledge graphs, rule-based reasoning, and search algorithms.
  • Construct resilient agent architectures with built-in mechanisms for error recovery and self-correction in production.
  • Integrate large language models (LLMs) and predictive models into systems that support complex financial decision-making.
  • Build APIs, tools, and microservices to connect AI capabilities with enterprise applications at scale.
  • Optimize AI systems for low latency and high throughput using response streaming and token usage optimization.
  • Provide technical leadership and mentor junior engineers on AI best practices and engineering excellence.

What we're looking for

  • 7 or more years of professional experience in software development and system design for large-scale production systems.
  • Proficiency in Python and SQL.
  • Experience building production-quality Agentic AI solutions using frameworks like LangChain, LlamaIndex, or equivalent tools.
  • Practical experience developing multi-agent systems using frameworks such as Google ADK, LangGraph, AutoGen, or CrewAI.
  • Advanced skills in Prompt and Context Engineering to optimize information for high-quality model performance.
  • Experience working with Vector Databases for AI retrieval and memory architectures.
  • Experience in the financial services industry, specifically in Funds Transfer, Pricing, Hedging, or Treasury technology (preferred).
  • Proficiency in Java as a secondary programming language (preferred); Master's degree in Computer Science or related field (preferred).

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