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
Distributed Systems @ 7
LLM @ 3
Machine Learning
Security @ 4
Technical Leadership
- 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
NVIDIA is seeking a Distinguished Engineer to serve as the founding technical leader for its AI Safety & Security Engineering team.
In this foundational role, you will take full ownership of the core harness architecture and baseline engineering standards, guiding the program from early-stage prototypes into a dependable, reviewable production pipeline. Your technical roadmap will dictate how NVIDIA designs, tests, and validates its safety-critical AI systems.
Technical leadership is fundamentally collaborative. You will work side-by-side with engineering managers, security partners, and evaluation teams to build consensus through active listening and transparent reasoning.
Beyond system design, teaching and mentorship are primary components of the position. You will actively review designs across the organization, keeping code quality and safety standards highly visible without hindering engineering velocity.
Ultimately, the architectural frameworks and team culture you establish early on will outlive any single component, shaping both the careers of founding engineers and the future of secure AI systems.
Responsibilities
- Architecture: Define the canonical harness architecture and component baseline.
- Engineering standards: Set the engineering standards the team builds on.
- Technical roadmap: Guide the Find, Validate, and Patch technical roadmap.
- Mentorship: Mentor founding engineers and support their growth.
Requirements
- Bachelor's degree (or equivalent experience) with 18+ years designing and building complex systems.
- Architecture depth: Deep experience architecting distributed systems, ML pipelines, or large-scale platforms.
- Research to production: A record of turning research into production-grade engineering.
- Collaboration: Ability to align engineers and researchers on one technical direction.
Ways to Stand Out from the Crowd
- Security exposure: Vulnerability research or security engineering experience.
- Agent systems: Familiarity with agent frameworks or LLM-based tooling.
- Evaluation: Experience building evaluation or benchmarking infrastructure.
Benefits
- Competitive salaries.
- Eligible for equity and benefits.