Chief AI Officer
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 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 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
- Good 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