About the Role
Strong product leadership and end-to-end product ownership in a capital-intensive technology business.

Key Responsibilities
& Measure of Success Product Strategy and Portfolio Ownership: Maintain a coherent portfolio across dedicated GPU clusters, bare-metal and virtual GPU services, training and inference infrastructure, AI workspaces, tokens, APIs, models, platform services and managed AI solutions Product Economics Capacity Strategy and Pricing: Translate market demand and the qualified sales funnel into product capacity requirements and provide inputs for GPU, storage, network, software and data center investments. Shakti Studio and AI Platform Business:
• Build and commercialise the model catalogue and token factory across open-source, sovereign and partner models.
• Develop offerings for inference APIs, token-based consumption, model fine-tuning and deployment, retrieval-augmented generation, AI agents, workflow orchestration and managed AI solutions.
• Define developer experience, onboarding, metering, API management, observability, model governance and platform-operating requirements.
• Drive product adoption across developers, startups, enterprises and government users and use consumption data and feedback to improve the platform.
• Create partnerships with model providers, ISVs, SaaS companies and solution providers through licensing, marketplace, co-sell and revenue-sharing models. Strategic Alliances and Ecosystem Development Build strategic relationships across accelerator, server, storage, networking, software, model, cloud, consulting,



research and financing ecosystems. Leadership and Stakeholder Management: Define transparent accountability and operating interfaces between Product and Yotta’s Sales, Solutioning, technology, operations, finance, legal, procurement and marketing functions. Governance Risk and Compliance: Ensure that AI and cloud services are designed and operated in line with applicable sovereignty, data-residency, security, privacy and responsible-AI requirements. Required Skills
• Strong product leadership and end-to-end product ownership in a capital-intensive technology business.
• Commercial understanding of GPU Cloud, accelerated computing, capacity economics and consumption-based services.
• Working knowledge of AI training, fine-tuning, inference, model serving, token economics, AI platforms and agentic orchestration.
• Ability to translate technical capability into differentiated products, pricing models and repeatable revenue.
• Experience managing product requirements, roadmaps, launches, adoption, utilisation, yield, margins and return on product investment.
• Strong product-management,



product-marketing and commercialisation capability across infrastructure and platform services.
• Ability to support complex solutioning and sales pursuits without displacing Sales ownership.
• Ability to engage credibly with AI-native companies, enterprise CXOs, government stakeholders, global partners and technical decision-makers.
• Understanding of sovereign AI, data residency, security, regulatory requirements and enterprise-grade service delivery. Preferred Skills
• Positive to have: Leadership experience with a hyperscaler, cloud service provider, neocloud, AI platform provider, enterprise software company or digital-infrastructure business.
• Direct exposure to NVIDIA or other accelerated-computing ecosystems.
• Experience defining and commercialising GPU infrastructure products through dedicated, reserved, take-or-pay and on-demand models.
• Experience building a developer platform, model marketplace, inference service, API business or consumption-based software business.
• Exposure to sovereign cloud, government technology programmes, regulated industries and international enterprise customers.
• Familiarity with financing and investment models for large technology-infrastructure deployments. Qualifications
• Bachelor’s or master’s degree in engineering, computer science, information technology, business management or a related discipline.
• An MBA or equivalent management qualification from a reputed institution is desirable but not mandatory. Work Location
• Mumbai

📌 Chief AI Officer (Mumbai)
🏢 Yotta Data Services Private
📍 Mumbai