GenAI Full-Stack Engineer Lead

GenAI Full-Stack Engineer LeadWorking at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community and make a real impact.Job OverviewWe are seeking a results-driven Generative AI practitioner with end-to-end experience for the execution and deployment of cutting-edge Generative AI and agentic AI solutions across our enterprise-wide Controls Technology platform.

In this role, you will be responsible for translating AI strategy into tangible, production-ready capabilities that enhance operational efficiencies and drive business value. We're looking for someone who combines deep technical expertise in generative AI — including context engineering, retrieval systems, knowledge graphs, and multi-agent orchestration — with a proven track record of successfully delivering complex technology projects. This role centers on architecting and delivering solutions built on pre-trained and hosted foundation models, not on training or fine-tuning models.Key ResponsibilitiesGenAI Delivery Leadership: Execute the delivery roadmap for generative and agentic AI projects, ensuring alignment with business objectives and timelines.

Manage the project lifecycle from ideation and scoping to deployment and post-launch support.Team Leadership & Mentorship: Build, mentor, and manage a high-performing team of AI engineers and specialists. Foster a culture of execution, collaboration, and continuous improvement to successfully deliver on the AI roadmap.End-to-End Solution Delivery: Oversee the design, development, and deployment of robust, scalable, and production-ready GenAI and agentic applications. Ensure all solutions meet rigorous performance, security, and quality standards before and after deployment.Agentic Solution Delivery: Drive the design and delivery of agentic workflows and multi-agent systems, establishing standards for agent harnesses, orchestration patterns, and reliable long-running agent execution across the platform.Stakeholder & Program Management: Serve as the primary point of contact for GenAI delivery.

Manage stakeholder expectations, communicate project progress, identify and mitigate risks, and ensure on-time and on-budget delivery.Cross-Functional Partnership: Collaborate closely with Data Mesh, Cloud Architecture, MLOps/LLMOps, and business unit teams to ensure the seamless integration and operationalization of GenAI and agentic solutions into our existing technology ecosystem.Technical Excellence & Best Practices: Drive the adoption of best practices in software development (CI/CD), LLMOps, agent observability, and project management (Agile/Scrum) within the AI team to ensure efficient and repeatable delivery.Governance & Ethical Deployment: Implement and enforce robust governance and ethical AI frameworks throughout the delivery process — including guardrails, agent isolation/sandboxing, and responsible AI practices — ensuring compliance with data privacy standards and corporate policies.Technical SkillsProgramming Languages: Python (expert proficiency required)Python Packages: Transformers, LangChain, LlamaIndex, TensorFlow, PyTorch, Pandas, NumPy, Scikit-learn, Flask/Django, and other relevant data science, machine learning, and web development libraries.Deep Learning Frameworks: TensorFlow, PyTorchLLMs: Llama, Gemini, GPT, and other advanced LLMs.Vector Databases: Pinecone, Weaviate, Chroma, Faiss, PostgreSQL with vector extensions (pgvector).Cloud Platforms: AWS, Azure, GCPMLOps Tools: MLflow, Kubeflow, or similar.Containerization: Docker, KubernetesCI/CD Tools: GitHub Actions, Jenkins, or similar.Version Control: GitData Visualization & Reporting: Tableau, Power BI, matplotlib, seaborn.Databases: SQL and NoSQL databasesQualifications10+ years of overall experience.8+ years of experience in AI/ML, with at least 3 years in Generative AI (including agentic AI).5+ years of leadership experience managing technical teams and delivering complex software or AI solutions.Extensive hands-on experience with AWS services and infrastructure related to AI/GenAI.A strong portfolio of projects showcasing the successful delivery of AI solutions into a production business environment.Education:Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field (PhD preferred).