Citi—Lead Gen AI Engineer - Vice President

Job description

Description: Job Overview We are seeking an experienced Senior Generative AI Developer to help drive the design, development, and integration of state-of-the-art Generative AI and agentic AI solutions across our enterprise Controls Technology platform. You will collaborate with cross-functional teams, contribute deep technical expertise in context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration, and play a key role in delivering scalable, grounded AI solutions to enhance automation and operational efficiency. This role centers on architecting robust applications and agent systems on top of pre-trained and hosted foundation models — not on training or fine-tuning models. Key Responsibilities - Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions that address business challenges. - Architect advanced context engineering strategies — context layering, chaining, compression, pruning/offloading, and memory management — to maximize reliability, provenance, and token efficiency in production. - Design and implement advanced generative AI methods, including sophisticated prompt engineering and Retrieval-Augmented Generation (RAG). - Build and optimize RAG systems, including hybrid search, multi-vector retrieval, and re-ranking pipelines. - Design and implement knowledge graphs and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. - Architect agentic workflows and multi-agent systems using Google Agent Development Kit (ADK) and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. - Design robust agent harnesses — governance, constraints, feedback loops, state/session management, and execution controls that make long-running agent systems reliable and safe. - Integrate agents with tools and data via the Model Context Protocol (MCP) and orchestrate inter-agent collaboration and task delegation via the Agent2Agent (A2A) protocol. - Support the integration of GenAI and agentic applications into production environments, ensuring robust deployment, scalability, observability, and maintainability. - Contribute to the development and optimization of real-time and streaming AI solutions. - Stay current with the latest advances in generative and agentic AI and actively share knowledge with the team. - Ensure adherence to ethical AI guidelines, guardrails, agent isolation/sandboxing, data privacy, and compliance standards. - Mentor junior team members, provide code reviews, and foster a culture of technical excellence. Required Technical Skills - Deep, hands-on expertise in core generative AI concepts — foundation models, LLMs, embeddings, tokenization, and context-window management. - Advanced skills in prompt engineering and context engineering, including familiarity with prompt design tools/frameworks and dynamic context orchestration. - Strong experience building RAG systems, including chunking strategies, hybrid search, and multi-vector retrieval. - Practical experience designing knowledge graphs and Graph RAG pipelines (e.g., using graph databases such as Neo4j or ArangoDB) for relationship-aware, multi-hop retrieval. - Proven experience building agentic AI systems with Google ADK and/or comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI, OpenAI Agents SDK), including tool/function calling, planning, and memory. - Strong grasp of multi-agent orchestration patterns (supervisor/worker, hierarchical, peer-to-peer) and harness engineering (governance, feedback loops, execution controls, agent isolation/sandboxing). - Hands-on experience with agent interoperability protocols — the Model Context Protocol (MCP) for tool/data access and the Agent2Agent (A2A) protocol for inter-agent collaboration. - Experience with agent observability and evaluation (e.g., tracing, OpenTelemetry-based tooling) for production agent systems. - Proficiency with major GenAI APIs (OpenAI, Gemini, Claude, etc.) and orchestration frameworks such as LangChain and LlamaIndex. - Strong skills in NLP (NER, dependency parsing, text classification, topic modeling). - Proficiency with vector databases and embedding models for large-scale retrieval. - Experience with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for AI/agentic applications. - Solid understanding of AI compliance, guardrails, and responsible AI practices. - Strong skills in Python and experience with data preprocessing, document ingestion, and API development. Required Soft Skills - Strong collaboration skills to work effectively in cross-functional teams. - Analytical and proactive approach to problem-solving. - Clear communication skills for both technical and non-technical audiences. - Eagerness to learn, innovate, and mentor less experienced developers. Qualifications - Bachelor's or master's degree in Computer Science, Data Science, AI, or a related field. - 5–7 years of experience in AI/software development, including significant experience in Generative AI and agentic AI. - Demonstrated portfolio of successful AI-driven projects in a business environment. - Experience working with AWS (or equivalent) cloud infrastructure for AI/GenAI. ------------------------------------------------------ Job Family Group: Technology------------------------------------------------------ Job Family: Applications Development------------------------------------------------------ Time Type: Full time------------------------------------------------------ Most Relevant Skills Please see the requirements listed above.------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------ 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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