Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 6
CI/CD
CUDA @ 4
Debugging
GPU @ 4
Hiring @ 4
LLM @ 4
LangChain @ 3
Machine Learning
Performance Analysis
PyTorch @ 6
Python @ 6
Security @ 6
Spark @ 4
TensorRT @ 4
vLLM @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Artificial intelligence is moving from passive assistance to agents that can reason, use tools, and complete work on a person's device. NVIDIA is building the software foundation that helps developers and partners deliver these experiences privately, efficiently, and responsibly across GeForce RTX, NVIDIA RTX PRO, RTX Spark, DGX Spark, and DGX Station systems.
The Engineering Manager will build and lead the team developing local and hybrid AI agent technology. The role sets technical direction, grows engineers, and delivers production software spanning agent runtimes, local inference, Windows integration, developer tools, and security controls. The team will turn lessons from Hermes, OpenClaw, Perplexity, and domain-specific agents into platform capabilities that work across NVIDIA systems.
Responsibilities
- Lead the architecture and implementation of local AI agent runtimes on Windows and NVIDIA RTX systems, with clear interfaces across models, tools, GPU software, operating-system services, and applications.
- Guide hands-on development through prototypes, design and code reviews, performance analysis, and debugging; help the team turn research ideas into reliable C++ and Python software.
- Build core agent capabilities including MCP and tool routing, persistent memory, skills, scheduling, multi-agent coordination, computer use, and policy-aware local or hybrid model routing.
- Own CI/CD, evaluation, compatibility, and regression systems across Windows releases, drivers, GPUs, models, and agent frameworks; add telemetry and diagnostics that make failures reproducible.
- Partner with AI research, GPU and driver, Windows platform, product security, Microsoft, OEM, ISV, and open-source teams to land durable interfaces and production integrations.
- Hire and develop engineers, set a high technical bar, allocate capacity, and create an environment where the team can make sound decisions and deliver maintainable software.
Requirements
- Bachelor's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
- 10+ years of software engineering experience, including 3+ years managing engineers or leading a comparable technical organization.
- Experience hiring and developing engineers, setting goals, providing useful feedback, and building an inclusive team environment.
- A record of delivering complex software platforms or systems from architecture through production operation.
- Technical fluency in AI agents, model inference, systems software, and local or hybrid deployment, with the judgment to guide architecture and execution.
- Ability to align engineering, research, product, security, and external partners around clear decisions and measurable outcomes.
- Proficiency with C++ or Python.
Preferred Qualifications
- Hands-on experience with Windows internals, process isolation, virtualization, containers, or sandboxing.
- Familiarity with OpenClaw, Hermes, LangChain, or similar agent frameworks; MCP; memory, skills, multi-agent, or computer-use patterns.
- Experience with TensorRT-LLM, Ollama, llama.cpp, vLLM, PyTorch, ONNX Runtime, Windows ML, model optimization, or quantization.
- Experience with CUDA, GPU performance, local models on consumer hardware, or privacy-aware inference routing.
- Experience contributing to open-source projects or working with Microsoft, OEMs, ISVs, and developer communities.
Compensation and Benefits
The base salary range is USD 224,000–356,500 for Level 3 and USD 272,000–431,250 for Level 4. Base salary is determined by location, experience, and the pay of employees in similar positions. The role is also eligible for equity and benefits.
Applications will be accepted at least until August 28, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.