The Lead Agentic AI Engineer will drive the design, development, and integration of advanced Generative AI and agentic AI solutions within the enterprise Controls Technology platform. This role involves collaborating with cross-functional teams and leveraging deep technical expertise in context engineering, retrieval systems, and multi-agent orchestration. The focus is on architecting robust applications and agent systems using pre-trained foundation models, rather than training or fine-tuning models. The engineer will also mentor junior team members and ensure adherence to ethical AI guidelines.

• 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.
• Deep, hands-on expertise in core generative AI concepts such as foundation models and LLMs.
• Advanced skills in prompt engineering and context engineering.
• Strong experience building RAG systems and designing knowledge graphs.
• Proven experience building agentic AI systems with Google ADK or comparable frameworks.
• Strong grasp of multi-agent orchestration patterns and harness engineering.
• Hands-on experience with agent interoperability protocols.
• Experience with agent observability and evaluation for production agent systems.
• Proficiency with major GenAI APIs and orchestration frameworks.
• Strong skills in NLP and proficiency with vector databases.
• Experience with containerization, orchestration, and CI/CD pipelines for AI applications.
• Solid understanding of AI compliance, guardrails, and responsible AI practices.
• Strong skills in Python and experience with data preprocessing and API development.

• Collaborate with AI architects, leads, and stakeholders to design and implement generative and agentic AI solutions.
• Architect advanced context engineering strategies to maximize reliability and token efficiency in production.
• Design and implement advanced generative AI methods, including sophisticated prompt engineering and RAG.
• Build and optimize RAG systems, including hybrid search and multi-vector retrieval.
• Design and implement knowledge graphs and Graph RAG architectures for multi-hop reasoning.
• Architect agentic workflows and multi-agent systems using Google ADK and comparable frameworks.
• Design robust agent harnesses to ensure reliability and safety of long-running agent systems.
• Integrate agents with tools and data via the Model Context Protocol and orchestrate inter-agent collaboration.
• Support the integration of GenAI and agentic applications into production environments.
• 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 share knowledge with the team.
• Ensure adherence to ethical AI guidelines and compliance standards.
• Mentor junior team members and provide code reviews.

• Citi offers a comprehensive benefits package including competitive pay, stock programs, healthcare coverage, retirement plans, paid time off, parental leave, and programs supporting employee wellbeing and professional development.