Vice President - 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.