GenAI Tech Lead - Senior Vice President

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*
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** 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.

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** 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.

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** 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.

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** 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.

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** 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.

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** 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.

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** 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*
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** 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).

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** 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.

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** Prompt Engineering:
** Adept at advanced prompt engineering techniques and best practices. Familiarity with frameworks that facilitate effective prompt design and management.

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** 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.

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** 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.

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** 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.

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** 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.

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** 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.

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** 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*
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** Delivery Leadership:
** Proven ability to lead and deliver complex, large-scale technical projects from concept to production.

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** Program Management:
** Expertise in Agile/Scrum methodologies, project planning, resource allocation, and risk management.

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** Strategic Execution:
** Capacity to translate high-level AI strategy into a concrete, actionable delivery plan and execute it effectively.

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** Stakeholder Management:
** Exceptional ability to manage expectations, communicate complex technical topics clearly, and build…