Lead GenAI Engineer

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.

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Job Family Group:

Technology

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Job Family:

Applications Development

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

Java (Programming Language).

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