Harness and Platform Engineer, AI Safety and Security Engineering
- Status
- Open
- Remote policy
- Remote
- Employment type
- Not stated
- Salary
- Not stated
- Categories
- Platform-Engineering, AI-Infrastructure-Engineering, Harness-Development, AI-Safety-Engineering, Software-Engineer, AI-Harness-Engineer, Senior-Safety-Technology-Engineer, Secure-AI-Systems-Engineer, Senior-Safety-Engineer, Safety-Systems-Engineer, Platform-Security-Engineer, Trust-and-Safety-Engineer, Senior-Machine-Learning-Engineer---Trust-and-Safety, Senior-AI-Platform-Engineer, Security-Platform-Engineer
- Source
- himalayas
- First observed
- 2026-08-14 17:54 UTC
- Last seen
- 2026-08-14 17:54 UTC
- Source claims posted
- 2026-08-14 17:29 UTC
- Consecutive misses
- 8 of 10
What the posting says
NVIDIA is widely recognized as one of the most desirable employers, with some of the most talented people in the world working for us! We believe open-weight models are foundational to American AI leadership and cybersecurity, and that trust in AI grows through participation, transparency, and broad scientific scrutiny. Our AI Safety & Security Engineering team builds and evaluates AI-powered tooling that helps find, validate, and patch software vulnerabilities. The agent harness and the platform it runs on are the substrate everything else builds on.
We are looking for a Harness/Platform Engineer to build that foundation. You will play a critical role in making the program's work possible, repeatable, and trustworthy. When a researcher runs an experiment, your platform decides whether the result can be reproduced tomorrow. Our current direction builds on NVIDIA NeMo agent tooling, and you will help shape where it goes. You will keep the whole loop visible, from environment to run to result. You will work closely with security research and evaluation engineers, learning their workflows and smoothing their paths. Good platform work here looks like fewer surprises: environments that behave, tooling that stays versioned, and runs that repeat. When something breaks, you will debug it with the people who felt it first. You will treat researcher time as precious and remove friction wherever you find it.
What You'll Be Doing:
Harness development:Design, implement, and maintain the agent harness.
Evaluation infrastructure:Build the systems we use to run and reproduce experiments.
Reproducibility:Own environments, tooling, and repeatable runs.
Collaboration:Partner with security and evaluation engineers on their workflows.
What We Need To See:
Bachelor's degree (or equivalent experience) with 5+ years of software engineering experience.
Technical core:Strong Python engineering plus comfort with containerized environments and CI/CD.
Infrastructure familiarity:Experience with agent frameworks, LLM orchestration, ML infrastructure, or evaluation harnesses.
Reproducibility instincts:Care for versioned tooling and repeatable results.
Ways to Stand Out from the Crowd:
NeMo experience:Hands-on work with NVIDIA NeMo or similar agent frameworks.
Security context:Exposure to security tooling or vulnerability research.
Developer experience:Building internal tools other engineers enjoy using.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until August 15, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
Originally posted on Himalayas
Quality
- x Salary range stated weight 35%
- + Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Based on 9 observation(s).
- + Days open - fineOpen for 0 days so far
- + Reopen count - fineNever reopened
- + Salary range removed after publication - fineSalary range has not been removed since publication
- + Salary range narrowed - fineSalary range has not narrowed since publication
- + Missing/reappear cycles - fineNo missing-then-reappeared cycles observed
Timeline
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#67052 2026-08-14 17:54 UTCPublished
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#82625 2026-08-15 09:56 UTCNot seenMiss 8 in a row