Lead Agentic AI Engineer Vice President

Citi

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Irving, TX
Salary
$125,760–$188,640 / yr
Posted
12 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $199k
This role $157k
$112k most similar roles pay here $253k

This role pays less than 75% of similar roles. Most pay $158,100–$239,503 — the shaded band above. At the midpoint, this role pays about $157k versus about $199k 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 · Lead Agentic AI Engineer Vice President

Lead Agentic AI Engineer – Vice President As part of the technology organization, this role involves architecting and delivering production-grade agentic AI systems that integrate large language models, retrieval-augmented generation, and full-stack engineering. You will build multi-tenant agentic ecosystems, develop custom fine-tuning applications, and create infrastructure for advanced RAG architectures including GraphRAG and RAPTOR. Day-to-day responsibilities include developing full-stack components using Python, Java with Spring Boot, and React to build internal dashboards and microservices. You will also implement Model Context Protocol servers and integrate graph and vector databases like Neo4j and pgvector. The role requires expertise in LLM orchestration, prompt engineering, and agentic frameworks such as LangChain or LangGraph. Working as a Forward Deployed Engineer, you will collaborate with subject matter experts to translate complex enterprise workflows into automated, agent-driven code within a high-scale financial environment.

What you'll do

  • Architect and deliver production-grade multi-agent systems using LLMs, RAG, and full-stack engineering.
  • Build and maintain full-stack applications using Python, Java (Spring Boot), and React for internal AI tools.
  • Develop and optimize multi-tenant agentic workflows using frameworks like LangChain, LangGraph, or Google's ADK.
  • Implement Model Context Protocol (MCP) servers to ensure secure, decoupled communication between agents and APIs.
  • Write data ingestion and retrieval code for advanced RAG architectures including GraphRAG and RAPTOR.
  • Integrate systems with vector and graph databases such as Neo4j and pgvector for complex data retrieval.
  • Design robust prompt engineering and classification logic to manage complex workflows and prevent intent collisions.
  • Collaborate with subject matter experts to translate complex business processes into automated, agent-driven code.

What we're looking for

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
  • 10+ years of professional software engineering experience.
  • 5+ years of experience in AI/ML, including at least 2+ years in Generative AI (LLMs, RAG, and Agentic workflows).
  • 3+ years of leadership experience managing technical teams and delivering complex software or AI solutions.
  • Deep hands-on expertise in Python, LLM orchestration, prompt engineering, and agentic frameworks like LangChain or LangGraph.
  • Proficiency in full-stack development using Java (Spring Boot) or Python (FastAPI) and React for frontend components.
  • Experience integrating applications with relational databases (Oracle), graph databases (Neo4j), and vector databases (pgvector, Pinecone, or Milvus).
  • Extensive experience with AWS services and infrastructure related to AI/ML deployment and scaling.

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