Lead Generative AI Developer

Citigroup Inc.; New York (NY); On-site; USD 177,000 - 265,000; Full time

Job summary

Citi in New York seeks a Lead Generative AI Developer to architect and implement GenAI and LLM solutions at scale. You will collaborate with operations, data engineers, product managers, and architects to deliver enterprise-grade AI capabilities across COO Technology.

The role is hands-on and requires building end-to-end GenAI pipelines, MLOps, and multi-agent orchestration with strong governance and data privacy adherence.

Qualifications

• 10+ years of professional software engineering experience, with at least 2+ years focused on Generative AI / LLM application development
• Python proficiency including async programming & API development (FastAPI, Flask)
• GenAI & LLM Stack with LangChain, LangGraph, LlamaIndex; Google Cloud AI Platform; RAG architectures; embeddings; prompt engineering; LLM APIs
• Machine Learning foundations; model evaluation, fine-tuning (LoRA, PEFT); inference optimization
• Cloud experience with AWS, Azure, or GCP
• SQL, NoSQL, vector databases (Pinecone, Weaviate, Chroma, pgvector)
• CI/CD, Docker, Kubernetes, Git; automated testing
• Banking/fintech experience is a plus

Responsibilities

• Design & Build GenAI Solutions: Architect end-to-end Generative AI pipelines incl. LLMs, RAG, autonomous agents, prompts
• Python Development: Build production-ready Python services and APIs
• Model Integration & Fine-tuning: Evaluate, integrate, and fine-tune LLMs and embeddings
• MLOps & Deployment: Create ML/GenAI deployment pipelines with observability and governance
• Agentic Workflows: Develop multi-agent orchestration for complex workflows
• Enterprise AI Governance: Align with AI Risk, Compliance, and data privacy standards
• Data Engineering: Design data pipelines; work with vector databases and enterprise data platforms
• Technical Leadership: Mentor engineers, review code, define GenAI standards
• Stakeholder Collaboration: Translate business needs into AI solutions with timelines

Skills

Python

LangChain

LangGraph

LlamaIndex

Prompt engineering

RAG architectures

LLM APIs

ML fundamentals

Cloud platforms

SQL

NoSQL

CI/CD

Docker

Kubernetes

Git

Google Cloud AI Platform

Education

Bachelor’s degree

Master’s degree preferred

Tools

Docker

Kubernetes

FastAPI

Flask

Git

MLflow

Job description

About the Role

We are looking for aLead Generative AI Developerto join our COO Technology Division in New York. In this high-impact role, you will architect, develop, and operationalize cutting-edge Generative AI and Large Language Model (LLM) solutions that directly transform how Citi's operational teams work. You will collaborate with cross-functional stakeholders - including operations leads, data engineers, product managers, and enterprise architects to deliver enterprise-grade AI capabilities at scale.

This is a hands-on engineering role for a builder who thrives at the intersection of applied AI research and production software engineering.

Key Responsibilities

• Design & Build GenAI Solutions:Architect and implement end-to-end Generative AI pipelines including LLM integrations, Retrieval-Augmented Generation (RAG) systems, autonomous AI agents, and prompt engineering frameworks.

• Python Development:Develop robust, scalable, and production-ready Python services and APIs that power AI-driven features across COO platforms.

• Model Integration & Fine-tuning:Evaluate, integrate, and fine-tune LLMs (e.g., GPT-5, Claude, Mistral) and embedding models for domain-specific financial use cases.

• MLOps & Deployment:Build and maintain ML/GenAI deployment pipelines using modern MLOps practices, ensuring reliability, observability, and governance.

• Agentic Workflows:Design and implement multi-agent orchestration frameworks (e.g., LangGraph, Google ADK) for complex, multi-step operational workflows.

• Enterprise AI Governance:Collaborate with Citi's AI Risk and Compliance teams to ensure all AI solutions align with regulatory requirements, responsible AI frameworks, and data privacy standards.

• Data Engineering:Design and optimize data pipelines feeding AI systems, working with vector databases (e.g., Pinecone, Weaviate, pgvector) and enterprise data platforms.

• Technical Leadership:Mentor junior developers, lead code reviews, and contribute to GenAI standards and best practices across the COO Technology organization.

• Stakeholder Collaboration:Translate complex business requirements from COO operations stakeholders into technical AI solutions, providing clear communication of trade-offs and timelines.

Required Qualifications

• Experience:10+ years of professional software engineering experience, with at least2+ years focused on Generative AI / LLM application development.

• Python:Expert-level Python proficiency — including async programming, API development (FastAPI, Flask), and software design patterns.

• GenAI & LLM Stack:

  • Deep hands-on experience with LLM frameworks:LangChain, LangGraph, LlamaIndex etc

  • Hands on experience with Google Cloud AI Platform

  • Proven experience withRAG architectures, embedding pipelines, and vector search

  • Strong understanding ofprompt engineering, few-shot learning, and chain-of-thoughttechniques

  • Experience integrating with LLM APIs:OpenAI, Azure OpenAI, Anthropic, AWS Bedrock, or Google Vertex AI

• Machine Learning:Solid grounding in ML fundamentals; familiarity with model evaluation, fine-tuning (LoRA, PEFT), and inference optimization.

• Cloud Platforms:Hands-on experience with at least one major cloud provider —AWS, Azure, or GCP— particularly managed AI/ML services.

• Data & Databases:Proficiency with SQL, NoSQL, andvector databases(Pinecone, Weaviate, Chroma, pgvector).

• Software Engineering Practices:Strong understanding of CI/CD pipelines, containerization (Docker, Kubernetes), version control (Git), and automated testing.

• Financial Services Acumen (Preferred):Prior experience in banking, fintech, or a regulated industry is a strong plus.

Preferred Qualifications

• Experience withmulti-agent orchestrationframeworks (MS AgentFramework, ADK, Strands, LangGraph)

• Familiarity withMLflow, Weights & Biases, or similarexperiment tracking and model management tools

• Knowledge ofresponsible AI practices: bias detection, explainability, hallucination mitigation

• Exposure toKafka, Spark, or Airflowfor data pipeline engineering

• Experience working in an Agile/SAFe delivery environment

• Advanced degree (M.S.) in Computer Science, AI/ML, or a related discipline — or equivalent demonstrated experience

Technical Stack (Working Knowledge Expected)

Languages: Python (expert), SQL, Bash

GenAI Frameworks: LangChain, LlamaIndex, LangGraph, Semantic Kernel

LLM Providers: OpenAI / Azure OpenAI, Anthropic, AWS Bedrock, Google Vertex AI

Vector Databases: Pinecone, Weaviate, pgvector, Chroma

Cloud: AWS / Azure / GCP

MLOps: MLflow, Docker, Kubernetes, GitHub Actions

Data Engineering: Spark, Airflow, Kafka

Databases: PostgreSQL, MongoDB, Redis

Education:

• Bachelor’s degree/University degree or equivalent experience

• Master’s degree preferred

Job Family Group:

Technology

Job Family:

Architecture

Time Type:

Full time

Primary Location:

New York New York United States

Primary Location Full Time Salary Range:

$176,720.00 - $265,080.00

In addition to salary, Citi's offerings may also include, for eligible employees, 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. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

Anticipated Posting Close Date:

Aug 19, 2026

Automated Processing and AI

We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.

Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.

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