Senior Software Engineer, Agentic Engineering

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

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NVIDIA

WebsiteLinkedInAll Job Openings

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

• develop a deep, shared understanding with NVIDIA's early-adopter engineering teams • identify the friction points where agentic workflows would have the highest impact • iterate with teams on proof points to validate or revise plans together • use technical judgment to distinguish durable architectural opportunities from "tech du jour" hype • agent-ify compiler infrastructure to enable autonomous agents to make high-dimensional optimizations • closed-loop validation on real hardware • integrate systems into git-native workflows and CI pipelines • contribute to cross-org collaborative group sharing reusable agentic methodology

🎯 Requirements

• MS in Computer Science, Engineering, or equivalent experience • 6+ years of experience • Strong Python development skills • Working knowledge of GPUs or other highly data-parallel systems • Demonstrated projects or work experience using and supporting AI systems • Track record of shipping complex projects with minimal direction, including raising challenges or syncing at the right moments • Experience building tools or systems shaped by direct partnership with internal customer or user teams • Examples of leading technical work through changing requirements and revising direction when evidence demands it • Experience in one or more of the following areas: Multi-agent orchestration frameworks (e.g., LangChain, LangGraph) or LLM-based workflow automation • Compiler infrastructure, intermediate representations, or program transformation • Autonomous search or optimization over high-dimensional parameter spaces • Hardware-aware performance optimization for deep learning workloads • Code generation systems or domain-specific languages (DSLs)

🏖️ Benefits

• equity • benefits