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Principal Generative AI Engineering Lead - Senior Vice President
Citigroup
4 hours ago
Full-time
On-site
Irving, Texas, United States
The USCC Architecture and AI Engineering group is seeking a seasoned and visionary prinicipal Generative AI/AI Lead to guide our team and architect the next generation of intelligent systems. This is a pivotal role in driving our AI project execution, from conceptualization through to production. We are looking for an expert with a proven track record in designing and delivering robust, scalable, and well-governed AI solutions. The ideal candidate will be a technical leader who can mentor a talented team of engineers, collaborate effectively with business stakeholders, and steer our technical direction in the rapidly evolving landscape of Generative and Agentic AI.
Key Responsibilities
Architect & Design: Lead the design and architecture of complex, end-to-end AI systems, ensuring they are scalable, resilient, maintainable, and secure. Strategize & Collaborate: Partner directly with business leaders and product managers to identify high-impact AI opportunities, define project roadmaps, and translate strategic business needs into a coherent technical vision. Lead & Mentor: Manage, mentor, and develop a team of AI engineers, fostering a culture of innovation, technical excellence, and rapid, continuous learning. Provide technical guidance and oversight on all projects. Govern & Standardize: Establish, implement, and enforce AI governance frameworks and MLOps best practices to ensure ethical, responsible, and compliant AI implementations across the organization. Hands-On Leadership: Remain hands-on in development, guiding the implementation of advanced machine learning, deep learning, and generative AI models and setting the standard for code quality. Drive Innovation: Champion research into emerging AI technologies, tools, and methodologies. Drive proof-of-concept initiatives and make strategic recommendations for integrating cutting-edge solutions. Oversee MLOps: Define and lead the strategy for MLOps, including the robust deployment, monitoring ,& full lifecycle management of AI applications in containerised environments like OpenShift. Required Skills and Qualifications
6+ years of experience in Gen AI application development, building and deploying solutions with large language models such as GPT, Gemini, Claude, and Llama. Leadership & Management: Proven experience in a technical leadership or team management role, with a strong ability to mentor engineers, manage project priorities, and drive team performance. Architectural Expertise: Demonstrated ability to design and architect scalable, high-availability, end-to-end AI and machine learning systems. Business Acumen: Significant experience collaborating with non-technical business stakeholders to identify opportunities, define requirements, and articulate a clear AI strategy. AI Governance: Strong understanding and practical experience in implementing governance, risk, and ethical guidelines for enterprise-grade AI solutions. Expert Python Proficiency: Expert-level programming skills in Python and its core AI/ML ecosystem (e.g., NumPy, Pandas, Scikit-learn). Deep AI/ML Expertise: Extensive, hands-on implementation experience with Machine Learning, Deep Learning, Generative AI, and Agentic AI systems. Advanced Data Expertise: Proven expertise in designing and managing complex data handling, preprocessing, and validation pipelines for mission-critical AI applications. Advanced MLOps: Deep, practical experience in MLOps, including containerization (Docker), orchestration (OpenShift/Kubernetes), CI/CD, and production deployment of AI models. Bachelor's degree or equivalent practical experience. Core Technical Stack & Expertise
The ideal candidate will have deep, hands-on expertise and strategic experience with the following technologies: LLMs: Gemini, OpenAI models (GPT series), Copilot, Claude, Llama, and experience with Local Models. Frameworks: LangChain, LlamaIndex, and the Hugging Face ecosystem (Transformers, Datasets, Tokenizers). Orchestration: LangGraph and designing and building complex Multi-Agent Systems. Development: Building production-grade, scalable services using Python, FastAPI, and asynchronous programming patterns. RAG (Retrieval-Augmented Generation): Designing and implementing advanced retrieval techniques using Vector DBs (e.g., Pinecone, Chroma) and PostgreSQL (with pgvector). ML/DL Platforms: PyTorch and/or TensorFlow for building and fine-tuning models at scale. Deployment & Monitoring: Containerization with Docker, deploying resilient production APIs, and implementing comprehensive monitoring, logging, and alerting strategies. Applied AI Skills: Mastery of Advanced Prompt Engineering, AI Workflow Design, and GenAI application optimization for cost, latency, and performance. The Ideal Candidate
You are a strategic thinker and a master builder , capable of seeing the long-term vision and diving deep into the technical details to make it a reality. You are an experienced and empathetic leader who empowers your team to do thei
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Architect & Design: Lead the design and architecture of complex, end-to-end AI systems, ensuring they are scalable, resilient, maintainable, and secure. Strategize & Collaborate: Partner directly with business leaders and product managers to identify high-impact AI opportunities, define project roadmaps, and translate strategic business needs into a coherent technical vision. Lead & Mentor: Manage, mentor, and develop a team of AI engineers, fostering a culture of innovation, technical excellence, and rapid, continuous learning. Provide technical guidance and oversight on all projects. Govern & Standardize: Establish, implement, and enforce AI governance frameworks and MLOps best practices to ensure ethical, responsible, and compliant AI implementations across the organization. Hands-On Leadership: Remain hands-on in development, guiding the implementation of advanced machine learning, deep learning, and generative AI models and setting the standard for code quality. Drive Innovation: Champion research into emerging AI technologies, tools, and methodologies. Drive proof-of-concept initiatives and make strategic recommendations for integrating cutting-edge solutions. Oversee MLOps: Define and lead the strategy for MLOps, including the robust deployment, monitoring ,& full lifecycle management of AI applications in containerised environments like OpenShift. Required Skills and Qualifications
6+ years of experience in Gen AI application development, building and deploying solutions with large language models such as GPT, Gemini, Claude, and Llama. Leadership & Management: Proven experience in a technical leadership or team management role, with a strong ability to mentor engineers, manage project priorities, and drive team performance. Architectural Expertise: Demonstrated ability to design and architect scalable, high-availability, end-to-end AI and machine learning systems. Business Acumen: Significant experience collaborating with non-technical business stakeholders to identify opportunities, define requirements, and articulate a clear AI strategy. AI Governance: Strong understanding and practical experience in implementing governance, risk, and ethical guidelines for enterprise-grade AI solutions. Expert Python Proficiency: Expert-level programming skills in Python and its core AI/ML ecosystem (e.g., NumPy, Pandas, Scikit-learn). Deep AI/ML Expertise: Extensive, hands-on implementation experience with Machine Learning, Deep Learning, Generative AI, and Agentic AI systems. Advanced Data Expertise: Proven expertise in designing and managing complex data handling, preprocessing, and validation pipelines for mission-critical AI applications. Advanced MLOps: Deep, practical experience in MLOps, including containerization (Docker), orchestration (OpenShift/Kubernetes), CI/CD, and production deployment of AI models. Bachelor's degree or equivalent practical experience. Core Technical Stack & Expertise
The ideal candidate will have deep, hands-on expertise and strategic experience with the following technologies: LLMs: Gemini, OpenAI models (GPT series), Copilot, Claude, Llama, and experience with Local Models. Frameworks: LangChain, LlamaIndex, and the Hugging Face ecosystem (Transformers, Datasets, Tokenizers). Orchestration: LangGraph and designing and building complex Multi-Agent Systems. Development: Building production-grade, scalable services using Python, FastAPI, and asynchronous programming patterns. RAG (Retrieval-Augmented Generation): Designing and implementing advanced retrieval techniques using Vector DBs (e.g., Pinecone, Chroma) and PostgreSQL (with pgvector). ML/DL Platforms: PyTorch and/or TensorFlow for building and fine-tuning models at scale. Deployment & Monitoring: Containerization with Docker, deploying resilient production APIs, and implementing comprehensive monitoring, logging, and alerting strategies. Applied AI Skills: Mastery of Advanced Prompt Engineering, AI Workflow Design, and GenAI application optimization for cost, latency, and performance. The Ideal Candidate
You are a strategic thinker and a master builder , capable of seeing the long-term vision and diving deep into the technical details to make it a reality. You are an experienced and empathetic leader who empowers your team to do thei
#J-18808-Ljbffr