Chief AI Officer

About the RoleStrong product leadership and end-to-end product ownership in a capital-intensive technology business.Key Responsibilities & Measure of SuccessProduct 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 solutionsProduct 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 DevelopmentBuild strategic relationships across accelerator, server, storage, networking, software, model, cloud, consulting, research and financing ecosystems.Leadership and Stakeholder Management:Define clear 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 SkillsStrong 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 SkillsGood 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.QualificationsBachelor’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 LocationMumbai