Lead GenAI Engineer

Job description

The Vice President (C13) – GenAI Sr Enginner. Citi's Banking Technology organization is seeking a talented and hands-on Senior AI Engineer to contribute to the design, development, and deployment of cutting-edge Generative AI and Agentic AI solutions for the banking sector. In this role, you will be responsible for implementing robust, scalable agentic AI workflows, integrating state-of-the-art LLMs, and building resilient full-stack applications that translate business requirements into production-grade systems.

The ideal candidate is an experienced, hands-on software engineer with strong technical depth in AI/ML principles, multi-agent frameworks, API design, and modern software engineering practices.

Key Responsibilities

Hands-on AI & Agent Development: Design, implement, test, and deploy scalable generative AI applications and agentic workflows for critical banking use cases, ensuring high performance, security, and reliability.

Full-Stack Implementation

Build end-to-end applications integrating front-end interfaces, backend services, and state-of-the-art LLM tools, APIs, and Model Context Protocol (MCP) integrations.

Rapid Prototyping & MVP Delivery

Champion an agile, MVP-first mindset to rapidly develop Proof of Concepts (POCs), run A/B experiments, iterate based on feedback, and accelerate time-to-value.

Evaluation & Observability

Implement evaluation metrics, guardrails, automated testing, and telemetry to benchmark agent behavior, response accuracy, and operational performance.

Collaboration & Engineering Standards

Collaborate closely with Lead Engineers, Data Scientists, Product Managers, and cross-functional teams; uphold best practices in code quality, automated testing, CI/CD, and peer reviews.

Continuous Learning & Innovation

Stay abreast of rapid advancements in LLMs, multi-agent orchestration frameworks, prompt engineering, and autonomous systems, applying relevant patterns to banking solutions. Qualifications & Technical Skills AI & Agentic Capabilities LLMs & Prompt Engineering: Solid working knowledge of enterprise LLMs (e.g., OpenAI/ChatGPT, Claude, Gemini, Llama) and prompt engineering techniques (chain-of-thought, few-shot prompting, RAG).

Must have in depth technical and hands on experience on RAG and Text2SQL usecases, Agentic Platform development, LLM parameter tuning and performance optimizations.

Agentic Frameworks

Hands-on experience with multi-agent orchestration frameworks (e.g., LangGraph, LangChain, AutoGen, CrewAI, or N8N).

MCP & Tool Integration

Practical experience implementing and integrating Model Context Protocol (MCP) or custom tool-calling interfaces into agentic systems.

Machine Learning Foundations

Working knowledge of ML frameworks/libraries (e.g., PyTorch, TensorFlow, Scikit-Learn, Pandas, NumPy).

Architectue

Backend Proficiency: Strong hands-on proficiency in Python (e.g., FastAPI, Flask, Django)

Databases & Data Storage

Experience working with relational and NoSQL databases (e.g., PostgreSQL, Oracle, MongoDB) as well as vector databases.

API & Architecture

Solid understanding of RESTful/gRPC API design, microservices, event-driven architectures, and distributed systems.

DevOps & Cloud Native

Hands-on experience with containerization and orchestration tools (Docker, Kubernetes) and CI/CD pipelines (Git, GitLab/Jenkins). Soft Skills & Industry Background Strong analytical and problem-solving skills with a pragmatic approach to technical challenges. Good communication and collaboration skills with experience operating in agile engineering teams. Experience in banking, financial services, or other highly regulated enterprise environments is a plus.

Experience & Education

Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related technical field (or equivalent practical experience).

Software Engineering Experience

7+ years of progressive software development experience with strong hands-on coding and delivery in production environments.

AI/ML Specialization

2+ years of dedicated experience developing and deploying AI/ML, Generative AI, LLM-powered applications, or agentic workflows. Proven track record of delivering resilient, high-quality features in an enterprise or production setting. ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills Java (Programming Language). ------------------------------------------------------ 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.

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