Assistant Vice President Software Engineer Gen AI

Citi

Confirmed live today High trust

Quick summary

Work type
On-site
Location
Irving, TX
Salary
$107,120–$160,680 / yr
Posted
3 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $185k
This role $134k
$93k most similar roles pay here $236k

This role pays less than 84% of similar roles. Most pay $148,650–$222,000 — the shaded band above. At the midpoint, this role pays about $134k versus about $185k 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 281 open roles on FindRole.

Listed pay typically runs $125,760–$188,640 across 263 roles with salary data.

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At a glance

TL;DR · Assistant Vice President Software Engineer Gen AI

Software Engineer GEN AI, Assistant Vice President joins the USCC Architecture and AI Engineering team to build and scale production components of an enterprise multi-agent AI platform. This role involves developing production AI agents for product analysis, requirements capture, UI prototyping, and automated code implementation. You will implement multi-agent workflows using the Google Agent Development Kit, integrate Gemini and Anthropic Claude via enterprise gateways, and build RAG pipelines utilizing vector search and embeddings. Key responsibilities include building evaluation harnesses, writing asynchronous Python, and developing FastAPI services with PostgreSQL session state. Required skills include advanced Python, prompt engineering, tool calling, and experience with Docker and Kubernetes. The role addresses the challenge of creating secure, reliable generative and agentic AI systems that operate within a highly regulated financial infrastructure to support the software delivery lifecycle.

What you'll do

  • Build and maintain production AI agents for product analysis, requirements capture, and automated code implementation.
  • Implement multi-agent workflows using Google Agent Development Kit including sub-agent orchestration and human-in-the-loop gates.
  • Integrate Gemini and Anthropic Claude models into pipelines using advanced prompt engineering and structured tool calling.
  • Connect AI agents to enterprise systems like JIRA and GitHub via MCP-style tool interfaces.
  • Develop RAG pipelines using vector search, embeddings, and clustering to ground responses in enterprise context.
  • Build evaluation harnesses using LLM-as-judge methods to measure faithfulness, relevancy, and hallucination rates.
  • Develop asynchronous Python services with FastAPI backed by persistent PostgreSQL session states.
  • Maintain CI/CD pipelines, containerized deployments, and automated testing for all production code changes.

What we're looking for

  • Bachelor's degree in Computer Science or a related field.
  • 3 to 7 years of hands-on software engineering experience (5+ for PhD holders) with a track record of shipping production software.
  • Strong computer science fundamentals including data structures, algorithms, complexity analysis, operating systems, networking, and relational database design.
  • Advanced Python skills including async programming, typing, dependency management, and solid practices like clean code and automated testing.
  • Hands-on experience with LLM application development, prompt engineering, tool/function calling, and multi-agent or agentic frameworks.
  • Practical RAG pipeline experience using vector databases, embedding-based retrieval, and structured LLM evaluation methods.
  • Experience integrating AI systems with external tools via structured interfaces and working knowledge of Docker and Kubernetes/OpenShift.
  • Experience with Google ADK, observability tooling, Go, React/TypeScript, or specific database technologies like ChromaDB (preferred).

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