AI Product Manager

The Product Manager will play a key role in driving Shakti Cloud's client-facing AI and GPU-powered services portfolio. This position requires a combination of deep technical knowledge and strategic market leadership to shape, deliver, and scale products that establish industry benchmarks in terms of performance, flexibility, and customer value. You will be actively engaged in all stages of the product lifecycle, from initial definition and prototyping to development, deployment, and shaping the go-to-market (GTM) and monetization strategies to ensure our offerings remain competitive and deliver tangible business results. Your primary responsibilities will include leading the vision, roadmap, and go-to-market strategy for AI and GPU compute products by integrating customer requirements, market insights, and engineering capabilities to create impactful solutions. The focus will span across various areas such as Bare Metal and Virtual Machines to model inference, fine-tuning, and advanced AI capabilities like agents, RAG (Retrieval-Augmented Generation), and workload customization, all supported by a resilient, cloud-native infrastructure. Key Responsibilities: 1. **Product Vision & Strategy** Define and drive the product strategy and roadmap for client-facing AI and GPU compute services. Develop features including Bare Metal, Virtual Machines, agents, fine-tuning, RAG, and customization capabilities. Align product vision with broader business objectives and evolving market opportunities. Promote innovation in inference, foundation model architectures, and AI application ecosystems. 2. **Market Analysis & Competitive Positioning** Conduct thorough market research on GPU compute trends, AI/ML workloads, and emerging technologies. Compare with competitors to identify whitespace opportunities and maintain a leadership position. Utilize market insights to shape monetization, pricing, and consumption models. 3. **Customer Engagement & Advocacy** Act as the primary advocate for customer requirements, from enterprise clients to AI-native startups. Translate customer feedback into actionable features and enhancements. Deliver workshops, demos, proposals, and pre-sales support to drive adoption. 4. **Monetization & Consumption Model Strategy** Develop innovative consumption models aligned with customer usage patterns. Optimize resource allocation and profitability through data-driven pricing and packaging strategies. Launch programs to drive adoption while maximizing ROI. 5. **Cross-Functional Leadership** Collaborate with various teams to ensure smooth product launches and lifecycle management. Ensure alignment on technical capabilities, market positioning, and business priorities. 6. **Performance Monitoring & Continuous Improvement** Monitor adoption, revenue, performance, and customer satisfaction metrics. Adjust strategies based on data insights and market dynamics. Skills and Qualifications: **Essential Skills** Technical expertise in AI-ML domain. Strong understanding of cloud management platforms, cloud-native architectures, and distributed computing. Proven success in managing technical products throughout their lifecycle. Ability to define and execute monetization strategies for infrastructure products. Excellent communication skills to influence both technical and business stakeholders. **Additional Domain Expertise (Highly Desirable)** Experience with deep learning, data science, and NVIDIA GPUs; exposure to other GPU ecosystems is a plus. Familiarity with inference engines and optimization techniques. Understanding of AI application ecosystems, inference serving, and workload orchestration. Prior experience in HPC or large-scale AI cloud environments. **Behavioral Attributes** Passionate about technology and pushing boundaries. Strategic thinker with the ability to delve into technical details. Customer-centric approach to guide continuous product improvement. Collaborative leader inspiring cross-functional teams towards a shared vision. **Qualification & Experience** Bachelor's or Master's Degree in Computer Science, Engineering, or related field. MBA is a plus. 8-10 years of professional experience, with at least 5 years in product management for cloud services, AI/ML, or GPU infrastructure. Proven track record in delivering innovative products and driving market adoption.,