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

  
  
  

1. 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. You will 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.

2. 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.

3. 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 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

  
  
  

------------------------------------------------------

------------------------------------------------------

------------------------------------------------------

------------------------------------------------------

------------------------------------------------------

------------------------------------------------------

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 review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.