Senior AI Leader

Job purpose : We are looking for a Senior AI Leader to head the AI Practice at Datamatics, driving enterprise-wide AI strategy, innovation, and delivery. This role will focus on leading teams in the design and implementation of AI-driven solutions, with a strong emphasis on Agentic AI, Retrieval-Augmented Generation (RAG), and enterprise-scale intelligent systems. The ideal candidate will bring a strong leadership background, guiding architecture, governance, and adoption of cutting-edge AI technologies across business functions. The ideal candidate will influence technology direction, shape presales strategy, and ensure alignment between AI innovation and business value realization. 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. Qualifications : - Education : Graduate - B.E/B.Tech - IT/CS. Requirements : - Overall 20+ years of experience in IT. - Proven experience in leading AI strategy, architecture, and delivery at an enterprise or practice level. - Deep knowledge of AI solution design principles, prompt optimization, and enterprise AI deployment models. - Exposure to at least one major cloud AI platform (AWS / Azure / GCP). - Strong familiarity with MLOps concepts and enterprise data/AI platforms. - Strong stakeholder management, communication, and cross-functional leadership skills. - Demonstrated ability to translate emerging AI capabilities into actionable business outcomes. - Strategic mindset with experience in building and scaling AI teams and practices. Technical & Domain Knowledge : - Strong understanding of LLM orchestration tools and frameworks. - Familiarity with vector databases and LLM APIs (OpenAI, Azure OpenAI, HuggingFace, Cohere). - Knowledge of AI solution design, prompt optimization, and deployment models. - Awareness of ML/DL frameworks and data engineering ecosystems. - Understanding of cloud-native and containerized environments for AI workloads. Leadership & Behavioral Skills : - Exceptional stakeholder management and executive communication ability. - Strategic mindset with the ability to convert emerging AI capabilities into business impact. - Track record of guiding cross-functional teams and influencing decisions.