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GenAI Tech Lead – Senior Vice President
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Citi

GenAI Tech Lead – Senior Vice President

Onsite Pune, India Junior
Posted 2 days ago
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Job Details

Job Overview

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, 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

  • Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field (PhD preferred).
  • Overall 14+ 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.

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Job Family Group:

Technology

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Job Family:

Data Architecture

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Time Type:

Full time

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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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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.

Required Skills
  • Large Language Models (LLMs)
  • Fine-Tuning
  • Model Optimization
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • Machine Learning Frameworks
Company Details
Citi
 
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