Senior Product Manager – Agentic Data Analytics

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Logo of NVIDIA

NVIDIA

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Artificial Intelligence • Gaming • Automotive

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• Define, own, and drive the product strategy for analytics in the agentic datacenter, connecting agent workflows, text-to-SQL, semantic context, query execution, and intelligent workload routing • Engage deeply with customers, partners, and open-source communities to discover underlying needs, owning the voice of the customer and incorporating insights into roadmaps and priorities • Establish success metrics and requirements for agentic analytics workflows where latency, throughput, cost, correctness, and infrastructure utilization all matter • Collaborate with Engineering, Research, DevRel, Field, and Enterprise teams to create agentic analytics architectures and reference blueprints • Serve as the point person for presenting vision, opportunities, and progress, setting expectations and managing internal and external collaborators

🎯 Requirements

• BS or MS Degree in a quantitative field (e.g., Computer Science, Applied Math, Computational Science, Engineering, etc.) or equivalent experience • 12+ years of product management, technical product strategy, or similar background in data analytics, data/AI infrastructure, or accelerated computing • Strong technical proficiency with databases, query engines, SQL, Python, and enterprise data platforms, with the ability to rapidly prototype agentic workflows, build proofs of concept, and get hands-on as a builder • Experience building agentic products or workflows for data analytics involving text-to-SQL, semantic layers, enterprise governance and security, iterative improvement cycles, etc. • Track record of crafting strategy in ambiguous technical markets, partnering across engineering/research/open-source ecosystems, and communicating value propositions clearly to technical and non-technical audiences

🏖️ Benefits

• equity • benefits

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