Role Overview
The role is responsible for leading end-to-end delivery of enterprise-scale AI, ML, and Generative AI solutions, ensuring production-grade deployments, governance, and measurable business impact. This position combines delivery leadership, GenAI architecture oversight, stakeholder management, and team leadership.
Key Responsibilities
- Own and lead the end-to-end delivery lifecycle of AI/ML and GenAI programsfrom problem definition and solution design to production deployment and post-go-live support.
- Lead and mentor cross-functional teams comprising data scientists, ML engineers, data engineers, and solution architects.
- Drive delivery of GenAI solutions, including LLM-based applications, RAG pipelines, prompt engineering, fine-tuning strategies, and Agentic AI use-cases.
- Establish and govern AI delivery frameworks, including MLOps / LLMOps, CI/CD pipelines, model lifecycle management, monitoring, and compliance.
- Partner with business and CXO stakeholders to translate business objectives into scalable AI solutions and ensure alignment throughout delivery.
- Ensure adherence to data governance, security, ethical AI, and regulatory standards.
- Identify delivery risks early and implement mitigation strategies to ensure quality, timelines, and cost efficiency.
- Drive innovation and continuous improvement, evaluating emerging AI/GenAI technologies and integrating them into delivery practices.
- Manage delivery budgets, resource planning, vendor partnerships, and stakeholder communications.
Required Skills & Qualifications
- 15+ years of experience in IT delivery, analytics, or data science, with 6+ years leading AI/ML and GenAI programs.
- Strong hands-on understanding of GenAI architectures, LLMs, RAG frameworks, and AI product delivery.
- Solid experience with cloud platforms (AWS, Azure, or GCP) and scalable AI deployments.
- Strong knowledge of MLOps / LLMOps, CI/CD, model deployment, and monitoring frameworks.
- Proven experience delivering enterprise-scale AI solutions with measurable business impact.
- Strong leadership, stakeholder management, and client-facing communication skills.
- Experience working in agile delivery environments.
