Gen AI Delivery Lead - SENIOR VICE PRESIDENT

  • Irving, TX
  • Posted 2 days ago | Updated 4 hours ago

Overview

On Site
USD 156,160.00 - 234,240.00 per year
Full Time

Skills

Project Lifecycle Management
Ideation
Team Leadership
Mentorship
Continuous Improvement
Roadmaps
Budget
Partnership
Collaboration
Cloud Architecture
Software Development
Project Management
Privacy
Large Language Models (LLMs)
Adapter
Multitasking
Optimization
Data Compression
Prompt Engineering
Cloud Computing
TensorFlow
PyTorch
Keras
Training
Parallel Computing
Natural Language Processing
Named-Entity Recognition (NER)
Text Classification
Modeling
Docker
Orchestration
Kubernetes
Continuous Integration
Continuous Delivery
Machine Learning Operations (ML Ops)
API
Real-time
Streaming
RESTful
Autogen
LangChain
LlamaIndex
Version Control
Git
Regulatory Compliance
Microsoft
Soft Skills
Program Management
Agile
Scrum
Project Planning
Resource Allocation
Risk Management
Stakeholder Management
Innovation
Problem Solving
Conflict Resolution
Analytical Skill
Generative Artificial Intelligence (AI)
Leadership
Management
Amazon Web Services
Machine Learning (ML)
Computer Science
Data Science
Artificial Intelligence
Data Architecture
Insurance
SEP
Law
Accessibility

Job Details

We are seeking a results-driven Generative AI Delivery lead to lead the end-to-end 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 a leader who combines deep technical expertise in generative AI with a proven track record of successfully delivering complex technology projects.

Key Responsibilities

  • GenAI Delivery Leadership: Define and execute the delivery roadmap for generative AI projects, ensuring alignment with business objectives and timelines. Manage the entire 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, DeepSpeed, 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 TensorFlow, 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 LangGraph, Autogen, Crew.ai, LangChain, LlamaIndex, 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 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 AI 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

  • 8+ years of experience in AI/ML, with at least 3 years in Generative 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/ML.

  • 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).

Job Family Group:
Technology

Job Family:
Data Architecture

Time Type:
Full time

Primary Location:
Irving Texas United States

Primary Location Full Time Salary Range:
$156,160.00 - $234,240.00

In addition to salary, Citi's offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire.

Most Relevant Skills
Please see the requirements listed above.

Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.

Anticipated Posting Close Date:
Sep 12, 2025

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.

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