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GenAI Tech Lead - Senior Vice President

Job in Irving, Dallas County, Texas, 75084, USA
Listing for: Citigroup Inc.
Full Time position
Listed on 2026-04-10
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 156160 - 234240 USD Yearly USD 156160.00 234240.00 YEAR
Job Description & How to Apply Below

We are seeking a results-driven Generative AI practitioner with end-to-end experience for execution and deployment of cutting-edge Generative 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 with a proven track record of successfully delivering complex technology projects.

Key Responsibilities
  • GenAI Delivery Leadership: Execute the delivery roadmap for generative 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 models. Ensure all solutions meet rigorous performance, security, and quality standards before and after deployment.
  • 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, and business unit teams to ensure the seamless integration and operationalization of AI models into our existing technology ecosystem.
  • Technical Excellence & Best Practices: Drive the adoption of best practices in software development (CI/CD), MLOps, 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, ensuring compliance with data privacy standards and corporate policies.
Required Technical Skills
  • Large Language Models (LLMs) & Fine-Tuning: Deep knowledge of LLMs and advanced fine‑tuning techniques. Proficient in Parameter-Efficient Fine-Tuning (PEFT) methods (LoRA, QLoRA, Adapter Tuning, Prefix Tuning), full fine‑tuning, instruction tuning, and agentic AI techniques (RLHF, multi‑task learning).
  • Model Optimization: Expertise in model compression and quantization methods (AWQ, GPTQ, GPTQ-for-LLaMA). Proficiency with optimized inference engines such as vLLM, Deep Speed, and FP6-LLM.
  • Prompt Engineering: Adept at advanced prompt engineering techniques and best practices. 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.
  • Machine Learning Frameworks and Cloud Computing: Proficiency in Tensor Flow, PyTorch, and Keras. Knowledge of distributed training, parallel processing, and extensive hands‑on experience with AWS services for AI/ML.
  • Natural Language Processing (NLP) and AI Deployment: Advanced NLP skills (NER, Dependency Parsing, Text Classification, Topic Modeling). Experience with Transfer Learning, Few-shot, and Zero-shot learning. Expertise in containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines for MLOps.
  • Data Science, Engineering, and API Development: Strong proficiency in data preprocessing, feature engineering, and handling large-scale datasets. Experience with real‑time AI applications, streaming data, and designing RESTful APIs for model integration.
  • Generative AI Tools & Platforms: Experienced with Lang Graph, Autogen, Crew.ai, Lang Chain, Llama Index, and Hugging Face Transformers. Familiarity with Gen AI APIs (OpenAI, Gemini, Claude) and version control systems like Git.
  • AI Compliance & Guardrails: Knowledge of AI compliance frameworks and best practices. Experience…
Position Requirements
10+ Years work experience
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