Used Tools & Technologies
Machine LearningRequired Skills & Competences
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.
Security @ 7
Kubernetes @ 4
GCP @ 4
Distributed Systems @ 4
Leadership @ 4
AWS @ 4
Azure @ 4
Technical Leadership @ 4
HTTP @ 4
Oracle @ 4
GPU @ 4
AI @ 4
- 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 has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. As we venture into the limitless potential of AI, our GPUs are driving advancements in computers, robots, and self-driving cars that understand the world. Joining the team means crafting the future of computing in a diverse, encouraging environment where you can do your best work and leave a lasting impact.
Responsibilities
- Define and guide the complete security architecture for global cloud and datacenter infrastructure, ensuring strong protection of critically important AI workloads against advanced adversaries.
- Architect robust security frameworks for cloud infrastructure across public (AWS, Azure, GCP, Oracle) and private GPU/AI environments.
- Implement network segmentation strategies using SDN techniques to enforce multi-tenant isolation.
- Facilitate adoption of Confidential Computing and hardware-rooted trust models for high-sensitivity AI workloads.
- Craft layered encryption schemes to mitigate risks and adhere to Zero Trust principles.
- Govern workload identity frameworks to eliminate static credentials and implement identity-based access controls.
- Direct security architecture for container and Kubernetes environments to maintain secure, scalable multi-tenant clusters.
- Provide technical leadership and mentor a team of security architects and engineers to drive architectural improvements across the organization.
Requirements
- 15+ years in security engineering or architecture roles with a minimum of 8 years in senior leadership positions.
- Expertise in architecting security for both “Security of the Cloud” and “Security in the Cloud.”
- Deep knowledge of cloud-native security architectures on major cloud platforms (AWS, Azure, GCP, Oracle).
- Strong expertise in workload identity and zero-trust access patterns.
- Demonstrated expertise in protecting containerized and Kubernetes environments at large scale.
- Ability to communicate complex security risks and architectural trade-offs to technical and management collaborators.
- BS/MS/PhD in Computer Science, Electrical Engineering, or related field, or equivalent experience.
Ways to stand out
- Experience securing AI/ML infrastructure and GPU compute clusters against novel threats.
- Experience with hardware-rooted trust and secure provisioning pipelines.
- Depth in post-quantum cryptography and applied cryptography in distributed systems.
Compensation & Benefits
- Base salary range: 272,000 USD - 431,250 USD (determined based on location, experience, and pay of employees in similar positions).
- Eligible for equity and a comprehensive benefits package (see https://www.nvidia.com/en-us/benefits/ and http://www.nvidiabenefits.com/).
Other information
- Applications for this job will be accepted at least until May 10, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and is committed to fostering a diverse work environment.