NVIDIA is powering the AI transformation of every industry through accelerated computing, AI software, cloud-to-edge platforms, simulation, and full-stack AI infrastructure. This role will lead NVIDIA's strategic partner engagement with India's major conglomerates, helping them identify, build, and scale AI workloads across business units.

The ideal candidate is a senior technical business leader who understands enterprise transformation, industrial workloads, cloud and data center infrastructure, and strategic account orchestration. This person will work across NVIDIA sales, product, engineering, solution architecture, software, marketing, and partner teams to turn executive-level interest into deployable, scalable AI outcomes.

What You'll Be Doing:

• Build and execute a strategic engagement plan for major Indian conglomerates and industrial AI accounts.

• Develop executive and technical relationships with CIOs, CTOs, business unit leaders, AI platform teams, innovation teams, and developers.

• Identify high-value workloads such as private AI, enterprise copilots, accelerated analytics, digital twins, simulation, predictive maintenance, industrial computer vision, and manufacturing intelligence.

• Help partners understand and adopt NVIDIA platforms across cloud, data center, edge, and industrial environments.

• Coordinate cross-functional NVIDIA teams around account strategy, technical enablement, executive engagement, and lighthouse opportunities.

• Run workshops, solution days, technical architecture reviews, and business-unit-specific enablement sessions.

• Develop repeatable use cases that can scale across multiple businesses within large groups.

• Capture account requirements, technical blockers, competitive dynamics, and product feedback for internal stakeholders.

What We Need To See:

• Bachelor's degree in engineering, computer science, business technology, or a related technical discipline, or equivalent experience.

• 10+ years of experience in strategic partnerships, enterprise technology, solution architecture, technical sales, business development, product management, or developer ecosystem roles.

• Strong understanding of enterprise AI, private AI, cloud infrastructure, data platforms, modern application architecture, and AI deployment lifecycles.

• Ability to engage senior executives and hands-on engineering or architecture teams with equal credibility.

• Experience operating across complex matrixed organizations involving sales, technical, product, marketing, and partner teams.

• Strong commercial judgment, structured account planning skills, and ability to translate technical value into business outcomes.

• Excellent communication, stakeholder management, and execution skills.

• Working familiarity with NVIDIA AI Enterprise, NVIDIA NIM, Triton Inference Server, TensorRT, TensorRT-LLM, CUDA, NGC containers, NVIDIA GPU Operator, and cloud/data center deployment patterns.

• Ability to position NVIDIA software across private AI, industrial AI, digital twins, simulation, accelerated analytics, computer vision, and enterprise AI factory initiatives.

• Familiarity with NVIDIA Omniverse, Isaac Sim, and synthetic data or simulation workflows where they apply to manufacturing, automotive, infrastructure, and industrial digital twin use cases.

• Ability to connect the right NVIDIA platform components to business-unit workloads and explain implementation paths to both executive and technical stakeholders.

Ways To Stand Out from the crowd:

• Experience with large Indian conglomerates or global strategic enterprise accounts.

• Knowledge of industrial AI, manufacturing systems, automotive technology, telecom infrastructure, digital twins, simulation, accelerated analytics, or private AI.

• Previous experience building joint solutions, executive programs, reference architectures, or multi-year strategic partnerships.

• Prior experience shaping executive or business-unit adoption plans around NVIDIA AI, data center, simulation, edge, or enterprise software platforms.

• Ability to create lighthouse use cases that can scale across multiple business units.