Lead Gen AI Engineer - Vice President
Citi (company site, opens in a new tab)5–7 yrsPuneHybridDirect career pageEst. 30–50 LPA
Posted on 4 Sept
Reach people at Citi
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Citi you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design and implement advanced Generative AI and agentic AI solutions integrated into enterprise Controls Technology platform.
- Architect and optimize systems including context engineering, Retrieval-Augmented Generation (RAG), knowledge graphs, multi-agent orchestration, and agent harnesses to enhance automation and operational efficiency.
- Ensure deployment scalability, observability, compliance with ethical AI standards, and mentor junior developers within AI-driven project environments.
Minimum Requirements
- 5–7 years of experience in AI or software development with significant Generative AI and agentic AI expertise.
- Bachelor's or master's degree in Computer Science, Data Science, AI, or related field.
- Proficiency in Python, containerization (Docker), orchestration (Kubernetes), CI/CD pipelines, and cloud infrastructure (e.g., AWS).
- Solid hands-on experience with Generative AI concepts, prompt and context engineering, RAG systems, knowledge graphs, agentic AI systems (Google ADK or equivalents), multi-agent orchestration, agent interoperability protocols (MCP, A2A), and GenAI APIs/frameworks (OpenAI, LangChain, LlamaIndex).
Ideal Candidate Profile
- Experienced technologist specializing in Generative AI and agentic AI systems with a strong background in architecting scalable production AI solutions.
- Demonstrates expertise in advanced multi-agent orchestration, knowledge graph application, and complex context engineering for reliable and efficient AI deployments.
- Capable of leading technical initiatives, ensuring AI compliance and ethical standards, and mentoring team members in a cross-functional environment focused on business-driven AI innovation.