Senior Solutions Architect, Agentic AI

🕒 July 22

🏄 California – Remote

🏄 California – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

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

• Architect, build, and ship end-to-end Agentic AI applications for M&E use cases • Act as a hands-on technical advisor and main domain expert during the pre- and post-sale stages • Work closely with customer AI researchers, engineers, and developers to build, prototype, and deploy Agentic solutions on NVIDIA platforms • Optimize inference performance and total cost of ownership using the full NVIDIA AI inference stack • Build hands-on proofs-of-concept, reference architectures, and reusable blueprints that serve as production templates • Partner with NVIDIA engineering, product, and sales teams to secure build wins and translate customer feedback into actionable product insights

🎯 Requirements

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, AI/ML, or a related field (or equivalent experience) • 8+ years as an ML/Software Engineer or Solutions Architect writing production-level code in Python and/or C/C++ in Linux environments • Validated experience building sophisticated agentic and multi-agent AI systems using orchestration frameworks • Solid understanding of MCP and A2A is vital • Strong background in PyTorch and distributed GPU (post-)training • Able to quickly prototype and build scalable GPU-accelerated architectures • Applies test-time compute, reinforcement learning, inference optimization, and post-training • Deploys workloads at scale on public cloud (AWS, GCP, Azure, OCI) or on-premise • Strong grasp of the M&E industry paired with excellent communication and presentation skills • Able to explain sophisticated ideas to both technical and non-technical groups • Works well with executives, partners, and engineering teams • Leads projects from start to finish in a fast-paced, multitasking setting.

🏖️ Benefits

• Competitive salaries • Comprehensive benefits package • Equity eligibility