Agentic AI Technical Lead

Citigroup Inc.; Jersey City (NJ); On-site; USD 142,320 - 213,480; Full time

Benefits offered by this job

Medical/Dental/Vision

401(k) Plan

Paid Time Off

Job summary

Citigroup Inc. in Jersey City seeks an Hands-On Technical Lead to guide Services AI Platform engineering. You will split your time between writing production-grade code and shaping technical strategy, building scalable multi-tenant agentic systems.

This role requires strong leadership, deep AI/ML experience, and the ability to translate complex business workflows into automated solutions while collaborating with SMEs and UI teams.

Qualifications

• 10+ years of professional software or systems engineering experience.
• 5+ years in AI/ML with at least 2+ years in Generative AI.
• 3+ years in leading technical teams delivering complex software/AI solutions.
• Extensive hands-on experience with AWS AI/ML services and infrastructure.
• Strong portfolio of production AI projects.

Responsibilities

• Lead and mentor an engineering team while coding production-grade components.
• Architect and implement multi-tenant agentic platform components with secure data flows.
• Collaborate with SMEs to translate enterprise workflows into automated, agent-driven code.
• Ensure integration with UI and enterprise APIs for seamless backend connections.

Skills

Leadership

AI/ML expertise

AWS

Production software

Enterprise collaboration

Education

Bachelor's or Master's in Computer Science/Data Science/AI

Tools

Neo4j

pgvector

Job description

Overview

We are seeking an expert Hands‑On Technical Lead to serve as the player‑coach for our Services AI Platform engineering team. In this role, you will split your time between writing production‑grade code and guiding the technical strategy of the platform. You will build and scale multi‑tenant agentic ecosystems, develop custom fine‑tuning applications, and ensure the platform adheres to our core principles (Trust, Adoption, Cost, Operations, and Scalability). You will lead by example, setting the standard for code quality and architectural purity while driving high‑impact business use cases.

Key Responsibilities

• Core Platform & Application Development
  • Full‑Stack Engineering: Lead the development of custom AI platform components, including full‑stack applications utilizing Python and Angular (e.g., building and maintaining internal LLM/SLM fine‑tuning planes and experiment tracking dashboards).
  • Agentic Frameworks: Code and optimize multi‑tenant intelligent agents utilizing modular orchestration patterns such as ReAct and ReWOO, and frameworks like Google’s Agent Development Kit (ADK).
  • Strict Architectural Implementation: Develop and enforce clean, decoupled integration layers. Build Model Context Protocol (MCP) servers ensuring a strict communication flow: Agents interact solely with MCP servers, and MCP servers interact solely with APIs to retrieve data. Direct database access from agents or MCP servers is strictly prohibited.
• Advanced Data Retrieval & Logic Engineering
  • Next‑Generation RAG: Write the data ingestion and retrieval code for advanced RAG architectures, including Knowledge Graph RAG (GraphRAG), LightRAG, and hierarchical summary trees (RAPTOR).
  • Vector & Graph Integrations: Develop seamless integrations with graph and vector databases such as Neo4j and pgvector to power complex, thematic data retrieval.
  • Prompt & Intent Engineering: Design robust LLM instructions and classification logic to prevent collisions in complex workflows, ensuring mutually exclusive intents are handled with high precision.
• Use Case Development & Forward Deployment
  • SME Collaboration: Act as a Forward Deployed Engineer (FDE), working directly with Subject Matter Experts (SMEs) on business and domain understanding to accurately translate complex enterprise workflows into automated, agent‑driven code.
  • Seamless Integration: Partner with UI and workflow integration developers to ensure the backend agentic logic connects flawlessly with user‑facing layers and existing enterprise APIs.

Qualifications

• 10+ years of experience
• 5+ years of experience in AI/ML, with at least 2+ years in Generative AI
• 3+ years of leadership experience managing technical teams and delivering complex software or AI solutions
• Extensive hands‑on experience with AWS services and infrastructure related to AI/ML
• A strong portfolio of projects showcasing the successful delivery of AI solutions into a production business environment

Education

• Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field

Benefits

Primary Location Full Time Salary Range: $142,320.00 – $213,480.00. In addition to salary, Citi’s offerings may also include discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays.

EEO Statement

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity, please review Accessibility at Citi. View Citi’s EEO Policy Statement and the Know Your Rights poster.