Generative AI Engineering Lead

We 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 Responsibilities** + **GenAI 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. **Required Technical Skills** + **Core Generative AI Concepts & Programming language:** Deep understanding of foundation models, LLMs, embeddings, tokenization, and context-window management. Fluent in applying pre-trained and hosted models to enterprise use cases. Hands on experience in Python. + **Context Engineering:** Expertise in advanced context engineering - context layering, chaining, compression, pruning/offloading, and memory management - to maximize reliability, provenance, and token efficiency in production. + **Prompt Engineering:** Adept at advanced prompt engineering techniques and best practices, with familiarity with frameworks that facilitate effective prompt design and management. + **Retrieval-Augmented Generation (RAG):** Advanced knowledge of RAG techniques, including hybrid search, multi-vector retrieval, Hypothetical Document Embeddings (HyDE), self-querying, query expansion, re-ranking, and relevance filtering. + **Knowledge Graphs & Graph RAG:** Experience designing and delivering knowledge graphs (e.g., using graph databases such as Neo4j or ArangoDB) and Graph RAG architectures to enable multi-hop reasoning, explainability, and traceable, grounded responses for high-value business domains. + **Agentic AI & Multi-Agent Orchestration:** Proven experience delivering agentic systems using **Google Agent Development Kit (ADK)** and comparable frameworks (LangGraph, Microsoft Agent Framework, CrewAI, OpenAI Agents SDK), applying orchestration patterns such as supervisor/worker, hierarchical, and peer-to-peer. + **Agent Harness & Interoperability:** Strong grasp of harness engineering (governance, constraints, feedback loops, execution controls, agent isolation/sandboxing) and agent interoperability protocols - the **Model Context Protocol (MCP)** for tool/data access and the **Agent2Agent (A2A)** protocol for inter-agent collaboration. + **Machine Learning Frameworks & Cloud Computing:** Working knowledge of ML frameworks and extensive hands-on experience with AWS (or equivalent) services and infrastructure for AI/GenAI. + **Natural Language Processing (NLP) & AI Deployment:** Advanced NLP skills (NER, dependency parsing, text classification, topic modeling). Expertise in containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for LLMOps. + **Data Engineering & API Development:** Strong proficiency in data preprocessing, document ingestion, and handling large-scale datasets. Experience with real-time and streaming AI applications and designing RESTful APIs for model and agent integration. + **Generative AI Tools & Platforms:** Experienced with LangGraph, Autogen, CrewAI, LangChain, LlamaIndex, Hugging Face, and Google ADK. Familiarity with major GenAI APIs (OpenAI, Gemini, Claude) and version control systems like Git. + **Agent Observability & Evaluation:** Experience with tracing and evaluation tooling (e.g., OpenTelemetry-based observability) for production GenAI and agent systems. + **AI Compliance & Guardrails:** Knowledge of AI compliance frameworks and best practices. Experience implementing guardrails to ensure ethical AI usage and mitigate risks (e.g., Microsoft's AI Guidance Framework). **Required Leadership & Soft Skills** + **Delivery Leadership:** Proven ability to lead and deliver complex, large-scale technical projects from concept to production. + **Program Management:** Expertise in Agile/Scrum methodologies, project planning, resource allocation, and risk management. + **Strategic Execution:** Capacity to translate high-level AI strategy into a concrete, actionable delivery plan and execute it effectively. + **Stakeholder Management:** Exceptional ability to manage expectations, communicate complex technical topics clearly, and build strong relationships with both technical and non-technical stakeholders. + **Pragmatic Innovation:** A passion for applying cutting-edge GenAI and agentic technologies to solve real-world business problems in a practical and efficient manner. + **Problem Solving:** Proactive and analytical mindset to overcome technical and logistical challenges in a fast-paced environment. **Qualifications** + Bachelor's or Master's degree in Computer Science, Data Science, AI, or a related field (PhD preferred). + 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. ------------------------------------------------------ **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._ _If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review_ _Accessibility at Citi (https://www.citigroup.com/citi/accessibility/application-accessibility.htm)_ _._ _View Citi's_ _EEO Policy Statement (https://www.citigroup.com/global/eeo-aa-policy)_ _and the_ _Know Your Rights (https://www.eeoc.gov/sites/default/files/2023-06/22-088\_EEOC\_KnowYourRights6.12ScreenRdr.pdf)_ _poster._ Citi is an equal opportunity and affirmative action employer. Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity.