VP, Applications Development, Tech Lead

Citi

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Tampa, FLIrving, TX
Salary
$113,840–$170,760 / yr
Employment
Full-time
Posted
36 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $185k
This role $142k
$101k $231k
below market most similar roles pay here above market

This role pays less than 78% of similar roles. Most pay $151,493–$218,812 — the blue band above. At the midpoint, this role pays about $142k 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 268 open roles on FindRole.

Listed pay typically runs $125,760–$188,640 across 251 roles with salary data.

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View all roles at Citi

At a glance

TL;DR · VP, Applications Development, Tech Lead

Role Posting Log in to save

VP, Applications Development – Tech Lead (Java, UI, PL-SQL & Agentic AI) joins the Applications Development team to drive the design, development, and integration of generative and agentic AI solutions across the enterprise Controls Technology platform. This role focuses on architecting robust applications and agent systems using pre-trained foundation models rather than training models. Key responsibilities include designing context engineering strategies, building RAG systems with hybrid search, and implementing knowledge graphs for multi-hop reasoning. You will build agentic workflows using Google ADK, LangGraph, or CrewAI, utilizing the Model Context Protocol and Agent2Agent protocols. Required technical skills include Python, NLP, vector databases, Docker, Kubernetes, and CI/CD pipelines. You will ensure production scalability, observability, and adherence to ethical AI guardrails while mentoring junior developers.

Skills

Generative AI Agentic AI Python RAG LangChain LlamaIndex LangGraph CrewAI Google ADK Neo4j ArangoDB Vector Databases OpenAI Gemini Claude Docker Kubernetes CI/CD AWS OpenTelemetry NLP

What you'll do

  • Architect advanced context engineering strategies including context layering, chaining, and memory management for production reliability.
  • Design and implement Retrieval-Augmented Generation (RAG) systems using hybrid search and multi-vector retrieval.
  • Build knowledge graphs and Graph RAG architectures to enable multi-hop reasoning and traceable responses.
  • Architect agentic workflows and multi-agent systems using frameworks like LangGraph, CrewAI, or Google ADK.
  • Design robust agent harnesses including governance, feedback loops, state management, and execution controls.
  • Integrate agents with tools and data using the Model Context Protocol (MCP) and Agent2Agent (A2A) protocols.
  • Deploy and maintain scalable generative AI applications ensuring observability, security, and adherence to ethical guardrails.

What we're looking for

  • Bachelor's or master's degree in Computer Science, Data Science, AI, or a related field.
  • 5+ years of experience in AI/software development, including significant experience in Generative AI and agentic AI.
  • Deep expertise in foundation models, LLMs, embeddings, tokenization, and context-window management.
  • Advanced skills in prompt engineering, context engineering, and building RAG systems with hybrid search and multi-vector retrieval.
  • Practical experience designing knowledge graphs and Graph RAG pipelines using databases like Neo4j or ArangoDB.
  • Proven experience building agentic AI systems using Google ADK, LangGraph, Microsoft Agent Framework, CrewAI, or OpenAI Agents SDK.
  • Hands-on experience with Model Context Protocol (MCP), Agent2Agent (A2A) protocols, and agent observability tools.
  • Proficiency in Python, NLP, vector databases, Docker, Kubernetes, CI/CD pipelines, and major GenAI APIs.

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