NVIDIA

Data Center Engineering and Operations

SeniorAIProductManager-DataCenterEngineeringandOperations

$208–328k Bengaluru, Karnataka, India FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior AI Product Manager - Data Center Engineering and Operations at NVIDIA. Skills: AI Product Management, Data Center Operations, AI/ML application techniques. Guide the entire lifecycle of AI-powered features and workflows within proprietary software and automation systems. Direct the product roadmap for AI features integrated within internal tools across the data center lifecycle (planning, procurement, deployment, operations, and decommissioning)”

What You'll Achieve.

Make AI capabilities visible, trustworthy, and embedded in routine tasks

Industry & Context.

Data Center Engineering and Operations

What They're Looking For.

Must Have

BS or MS degree in Computer Science, Computer Engineering, or equivalent experience, 12+ years in product management, software engineering or similar roles at a technology company serving enterprises, Practical experience with AI/ML application techniques, Experience working with Data Center Engineering and Operations infrastructure, data, and automated workflows, Background with managing vendor data pipelines such as ASN solutions and shop floor configuration details, Experience using AI coding tools like Cursor for prototyping, Proven success in leading engineering efforts using Agile sprints

Nice to Have

Experience using Agile methodology and ceremonies, Background using data from ERP systems like SAP for procurement and asset management, Experience performing or supporting data center operations roles such as procurement, site logistics, asset management or DC Ops technician activities

What You'll Do.

Guide the entire lifecycle of AI-powered features and workflows within proprietary software and automation systems

Direct the product roadmap for AI features integrated within internal tools across the data center lifecycle (planning

Identify new opportunities to deploy AI solutions using existing data

Prioritize opportunities based on feasibility and impact

Assemble user requirements for features and improvements driven by artificial intelligence

Conduct discovery sessions with internal collaborators to understand workflows

and where AI can help or automate processes

Transform these insights into detailed product requirements and user stories

Work closely with development and UX teams to guarantee AI functions are easily comprehended within existing internal tools and dashboards

Incorporate clear confidence indicators

Establish and sustain effective feedback channels with internal users

Identify user-facing controls and review procedures suitable for operational settings

How You'll Work.

Team & Collaboration

Join forces with software and data engineers, UI/UX designers, and data center associates; Work closely with development and UX teams

Process & Methodology

Agile sprints

Full Job Description

Join NVIDIA as a Senior AI Product Manager - Data Center Engineering and Operations, and contribute to pushing the boundaries of AI technology. This is your chance to create the next generation in managing data center environments with innovative and high-quality AI solutions! The Senior AI Product Manager will guide the entire lifecycle of AI-powered features and workflows within our proprietary software and automation systems. This role emphasizes AI solutions throughout the full data center lifecycle: from capacity and infrastructure planning to equipment procurement, asset intake and tracking, installation, maintenance, and decommissioning. You will join forces with software and data engineers, UI/UX designers, and data center associates. Together, this effort will make AI capabilities visible, trustworthy, and embedded in routine tasks. **What you 'll be doing:** * Direct the product roadmap for AI features integrated within internal tools across the data center lifecycle (planning, procurement, deployment, operations, and decommissioning). Identify new opportunities to deploy AI solutions using existing data. Prioritize opportunities based on feasibility and impact. * Assemble user requirements for features and improvements driven by artificial intelligence. Conduct discovery sessions with internal collaborators (data center engineers, operations leads, planning/procurement teams) to understand workflows, difficulties, and where AI can help or automate processes. * Transform these insights into detailed product requirements and user stories, for AI features. Work closely with development and UX teams to guarantee AI functions are easily comprehended within existing internal tools and dashboards. Incorporate clear confidence indicators, explanations, and controls. * Establish and sustain effective feedback channels with internal users. Identify user-facing controls and review procedures suitable for operational settings (e.g., suggestions needing human approval

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