Senior Engineer, Local AI – Agents and Systems

NVIDIA

Senior Engineer developing AI agent frameworks and optimizing runtimes for Windows on GeForce RTX. Leading engineering efforts and collaborating with internal AI research teams.

Posted 7/28/2026full-timeSanta Clara • California, Washington • 🇺🇸 United StatesSenior💰 $184,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing agent frameworks for Windows environments, with a strong focus on system-level security, AI orchestration, and multi-agent systems. Proficient in C++ and Python, with extensive experience in leading engineering teams and optimizing AI performance on consumer hardware.

Highest-signal resume keywords

Windows OS InternalsAI Orchestration FrameworksC++ ProgrammingPython ProgrammingLLM Inference Pipelines

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringSystem-Level Security ArchitectureGPU-Accelerated ComputingVirtualizationContainerizationSandboxing TechnologiesAI Agent DeploymentProcess IsolationPerformance-Critical SystemsMulti-Agent Systems

Soft Skills

MentoringCollaborationGuideline Establishment

Tools & Technologies

CUDATensorRTOpenClawHermesLangChain

Certifications & Qualifications

BS in Computer ScienceMS in Computer EngineeringPhD in Related Technical Field

Industry Keywords

AI AssistantsConsumer HardwarePrivacy FrameworksSecurity FrameworksTechnical Roadmap

Tech Stack

Tools & technologies

C++Python

About the role

Key responsibilities & impact

Act as the lead engineer for developing the agent frameworks natively on Windows environments.
You will build the technical roadmap to bring always-on, self-evolving AI assistants to GeForce RTX PCs and laptops.
Lead the engineering efforts to optimize the agent runtimes for Windows.
You will ensure that autonomous agents operate within detailed, policy-based privacy and security frameworks (e.g., handling filesystem access, secure inference routing, and network egress).
Partner closely with internal AI research teams, driver teams, and the open-source OpenClaw community.
Ensure our consumer hardware provides an excellent ecosystem for autonomous agents.
Foster a collaborative engineering culture by mentoring other engineers, establishing guidelines for AI agent deployment, and writing reliable, production-ready code.

Requirements

What you’ll need

10+ years of relevant professional software engineering experience, with at least 3+ years in Staff, or Lead Architect role.
BS, MS, or PhD in Computer Science, Computer Engineering, or a related technical field (or equivalent experience).
Deep understanding of Windows OS internals, process isolation, sandboxing technologies, and system-level security architecture.
Proven understanding of LLM inference pipelines (Ollama, Llama.cpp, vLLM), GPU-accelerated computing (CUDA, TensorRT), and experience running local models on consumer-grade hardware.
Practical experience with modern AI orchestration and agentic frameworks (e.g., OpenClaw, Hermes, LangChain) and an understanding of how multi-agent systems plan, act, and use tools.
Proficiency in multiple languages, particularly C++ (for performance-critical systems/OS integration) and Python (for AI/blueprint logic).
Experience building virtualization, containerization, or robust sandboxing tools natively for the Windows ecosystem.

Benefits

Comp & perks

equity
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