Overview In this senior role, you will lead the delivery of GenAI and agentic AI solutions across Citi's Controls Technology platform, translating AI strategy into production-ready capabilities. You will shape architecture and oversee end-to-end delivery, from ideation to post-launch support, collaborating with cross-functional teams to drive efficiency and business value. You'll focus on pre-trained and hosted models, establishing governance and best practices to ensure secure, scalable deployments. This position offers strategic ownership of a high-impact AI delivery program within a global financial institution.
Compensation / Benefits- hybrid work model
- leadership role with strategic ownership
- professional development opportunities
- competitive compensation
- comprehensive benefits package
- wellbeing resources
Responsibilities- Lead GenAI delivery roadmap and manage end-to-end project lifecycle (ideation to deployment)
- Build, mentor, and manage a high-performing AI engineering team
- Oversee design, development, and production deployment of GenAI and agentic applications
- Drive design and delivery of agentic workflows and multi-agent systems with standards for orchestration
- Serve as primary point of contact for GenAI delivery, manage stakeholders and risks
- Collaborate with Data Mesh, Cloud Architecture, MLOps/LLMOps, and business units for integration
- Promote best practices in CI/CD, LLMOps, agent observability, and Agile management
- Implement governance and ethical AI guardrails along with data privacy compliance
Key requirements- 6+ years in AI/ML with 3+ years in Generative AI (including agentic AI)
- Extensive hands-on experience with AWS services and related AI infrastructure
- Strong portfolio of production AI solutions
- Experience with pre-trained and hosted foundation models
- Familiarity with GenAI tooling and APIs (OpenAI, Gemini, Claude) and version control (Git)
- Knowledge of NLP, data preprocessing, APIs for model/agent integration
- Experience with RAG, knowledge graphs, and multi-agent orchestration
- Understanding of MLOps, LLMOps, and governance frameworks
- Delivery leadership
- Stakeholder management
- Strategic execution
- Foundation models, LLMs, embeddings, tokenization, context-window management
- Context engineering (layering, chaining, memory management)
- Prompt engineering and management frameworks
