Generative AI - Group Manager - Senior Vice President

Posted 7 Days Ago
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Jersey City, NJ, USA
In-Office
177K-265K Annually
Senior level
Fintech • Financial Services
The Role
Lead and deliver production-grade generative AI solutions: manage end-to-end model development, deploy scalable LLM systems, build and mentor AI teams, coordinate cross-functional integration (MLOps, Cloud, Data Mesh), enforce governance and ethical AI, and ensure on-time, on-budget delivery of GenAI capabilities.
Summary Generated by Built In

We are seeking a results-driven Generative AI group manager with end-to-end experience for execution and deployment of cutting-edge Generative AI solutions for Services Tech AI team . 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, 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:

  • 15+ Years experience

  • 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

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Job Family Group: Technology

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Job Family:Applications Development

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Time Type:Full time

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Primary Location:Jersey City New Jersey United States

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Primary Location Full Time Salary Range:$176,720.00 - $265,080.00


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.

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Most Relevant Skills Please see the requirements listed above.

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

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Anticipated Posting Close Date:Jun 25, 2026

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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.
View Citi’s EEO Policy Statement and the Know Your Rights poster.

Skills Required

  • 15+ years experience
  • 8+ years in AI/ML with at least 3 years in Generative AI
  • 5+ years leadership experience managing technical teams and delivering complex software or AI solutions
  • Deep knowledge of LLMs and advanced fine-tuning techniques (PEFT: LoRA, QLoRA, Adapter Tuning, Prefix Tuning), instruction tuning, agentic AI (RLHF)
  • Expertise in model compression and quantization methods (AWQ, GPTQ, GPTQ-for-LLaMA) and optimized inference engines (vLLM, DeepSpeed, FP6-LLM)
  • Advanced prompt engineering skills and familiarity with prompt frameworks
  • Advanced RAG techniques including hybrid search, multi-vector retrieval, HyDE, re-ranking, and relevance filtering
  • Proficiency with TensorFlow, PyTorch, and Keras
  • Extensive hands-on experience with AWS services and AI/ML infrastructure
  • Experience with containerization and orchestration (Docker, Kubernetes) and CI/CD for MLOps
  • Strong data preprocessing, feature engineering, and handling large-scale/streaming datasets; experience building real-time AI applications
  • Experience designing RESTful APIs for model integration
  • Practical experience with GenAI tools and platforms (LangGraph, Autogen, Crew.ai, LangChain, LlamaIndex, Hugging Face Transformers)
  • Familiarity with Gen AI APIs (OpenAI, Gemini, Claude) and version control (Git)
  • Knowledge of AI compliance frameworks, governance, and implementing guardrails (ethical AI, data privacy)
  • Proven delivery leadership and program management experience (Agile/Scrum) for large-scale technical projects
  • Strong stakeholder management and communication skills with technical and non-technical audiences
  • Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field
  • A strong portfolio of projects demonstrating production delivery of AI solutions

Citi Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Citi and has not been reviewed or approved by Citi.

  • Healthcare Strength Benefits coverage is positioned as comprehensive, including health, dental, and vision insurance plus on-site clinics, prescription drug support, and disability coverage. Family-building support such as fertility assistance is described as a notable differentiator within the overall package.
  • Retirement Support Retirement benefits are framed as strong, highlighted by a 401(k) with matching and additional plan options like a Roth 401(k). Financial support is reinforced through discounts and broader financial guidance resources tied to the benefits ecosystem.
  • Wellbeing & Lifestyle Benefits Wellbeing support extends beyond insurance through programs like an Employee Assistance Program, counseling/legal resources, and gym or wellness reimbursement. These offerings increase the perceived total rewards value even when cash compensation sentiment varies by role.

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The Company
HQ: Kwun Tong, Kowloon
223,850 Employees

What We Do

Citi's mission is to serve as a trusted partner to our clients by responsibly providing financial services that enable growth and economic progress. Our core activities are safeguarding assets, lending money, making payments and accessing the capital markets on behalf of our clients. We have 200 years of experience helping our clients meet the world's toughest challenges and embrace its greatest opportunities. We are Citi, the global bank – an institution connecting millions of people across hundreds of countries and cities.

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