Senior Python AI Engineer Agentic Systems

Citi

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Irving, TX
Salary
$107,120–$160,680 / yr
Posted
17 days ago
Freshness
Confirmed live 2 days ago
Closes
Sep 30, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $204k
This role $134k
$90k most similar roles pay here $263k

This role pays less than 95% of similar roles. Most pay $162,150–$246,150 — the shaded band above. At the midpoint, this role pays about $134k versus about $204k 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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View all roles at Citi

At a glance

TL;DR · Senior Python AI Engineer Agentic Systems

As a Senior Python-AI Engineer, Agentic Systems, you will join the Agentic AI engineering team to design and develop production-grade agentic systems for Funds Transfer Pricing and Financial Hedging platforms. You will take ownership of complex multi-agent architectures, building retrieval-augmented generation pipelines using vector databases, and implementing planning and reasoning capabilities through knowledge graphs and search algorithms. Your daily work involves constructing resilient architectures with self-correction mechanisms, integrating large language models into financial decision-making workflows, and developing APIs and microservices for enterprise integration. You will utilize Python, SQL, and frameworks like LangChain, LlamaIndex, Google ADK, LangGraph, AutoGen, or CrewAI. Key technical skills include prompt and context engineering, as well as optimizing systems for low latency and high throughput to solve critical problems in the financial services domain.

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 and predictive models into systems that support complex financial decision-making workflows.
  • 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.

What we're looking for

  • 4 or more years of professional experience in software development and system design for large-scale production systems.
  • Proficiency in Python and SQL.
  • Hands-on 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.
  • Applied knowledge of LLMs within agentic architectures, including designing and integrating APIs for AI services.
  • 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 financial services (preferred); proficiency in Java (preferred); Master's degree in Computer Science or related field (preferred).

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