Vice President - Senior AI Leader

Key responsibilities • Lead the AI Practice, defining the vision, roadmap, and strategy for AI adoption across the organization. • Oversee solution architecture and delivery of AI initiatives leveraging LLMs, RAG frameworks, and enterprise data platforms. • Provide thought leadership on emerging AI technologies, frameworks, and best practices. • Establish frameworks, governance, and reusable components for scalable AI implementation. • Establish AI architecture principles, standards, and governance frameworks across the organization. • Drive development of reusable solution accelerators, reference architectures, and best practices • Build and mentor a strong AI and data science team, fostering innovation and collaboration. • Represent the AI Practice in client discussions, steering PoCs and solution proposals for business impact. Architecture & Solution: • Oversee end-to-end design and delivery of AI solutions including agentic workflows, RAG systems, LLM-powered applications, and ML models integrated into enterprise platforms. • Guide architecture reviews, technical design validations, and PoC direction for AI initiatives. • Ensure alignment of AI solution design with cloud-native, microservices-based, and containerized deployment models. • Partner with enterprise data and ML teams to align AI strategy with organizational goals and data maturity. Innovation & Technology Leadership • Guide teams on leveraging tools such as LangChain, LlamaIndex, vector databases, and orchestration frameworks. • Promote adoption of modern MLOps practices including lifecycle management, deployment, monitoring, and evaluation of AI models. • Rapid innovation while ensuring enterprise-grade scalability and reliability. Stakeholder & Business Engagement • Collaborate with CXOs, business heads, and technology leaders to identify, prioritize, and execute AI opportunities. • Represent the AI Practice in client engagements, supporting solution proposals, PoCs, and RFP responses. • Translate complex AI concepts into clear strategic insights for senior stakeholders. CoE & Organizational Contribution • Contribute to the AI Center of Excellence by driving standardization, documentation, and knowledge sharing. • Establish evaluation frameworks for model performance, risk, and responsible AI usage. • Influence enterprise architecture decisions and cross-functional technology roadmaps.