Astera Labs Inc.
Sr. Principle Systems / Rack Thermal Engineer
Research Triangle Park, North Carolina, United States · Senior · Full-time
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About the role
- This is a highly visible technical leadership role responsible for defining thermal strategy across:
Responsibilities
- Develop thermal architecture from silicon devices through complete rack-scale AI systems.
- Drive architecture decisions balancing performance, reliability, power, density, and cost.
- Lead AI Rack and Platform Cooling Design
- Develop system-level cooling strategies supporting next-generation high-density AI deployments.
- Develop Advanced Air and Liquid Cooling Solutions
- Support advanced rack cooling technologies.
- Develop thermal strategies for future 100kW+ AI racks.
- Optimize thermal performance while reducing infrastructure cooling cost.
- Lead Optical Thermal Innovation
- Develop thermal solutions for:
Requirements
- 15+ years of thermal engineering experience.
- Proven track record leading thermal architecture for AI infrastructure, networking platforms, servers, storage, or hyperscale systems.
- Deep expertise in:
- Strong experience with thermal validation and correlation techniques.
Nice to have
- Experience supporting NVIDIA, AMD, or Intel-based AI platforms.
- Experience with Open Rack and OCP architectures.
- Expertise in liquid cooling technologies.
- Familiarity with PCIe Scale-Up and UALink systems.
- Experience with Ethernet scale-out networking.
- Experience supporting optical technologies including:
- Silicon Photonics
- Fiber Connectivity Systems
Skills
- PCIe Scale-Up Fabrics
- UALink Scale-Up Networks
- Ethernet Scale-Out Fabrics
- ESUN Network Architectures
- Advanced Fiber Connectivity Solutions
- GPU Compute Platforms
- Rack-Scale AI Systems
- Near Package Optics (NPO)
- Co-Packaged Optics (CPO)
- Air-Cooled and Liquid-Cooled Open Rack Platforms
Compensation
- The salary range is $195,000 to $250,000, depending on experience, level, and business needs.
This listing is sourced directly from Astera Labs Inc.'s careers page and normalized into a canonical job model.