Qualcomm
Sr. Staff Hardware Design Engineer, Rack Scale - Team Lead (AI Data Center)
$170K–$255K
Austin, Texas +2 · On-site · Senior Staff · Full-time · Posted Oct 27, 2026
- Location
- Austin, Texas
San Diego, California
Santa Clara, California - Experience
- 6+ years with a bachelor’s degree, 5+ years with a master’s degree, or 4+ years with a PhD in Hardware Engineering or related work experience; 8+ years in systems or hardware engineering, hardware project lifecycle management, and technical product/program management is listed under Preferred Qualifications.
- Education
- Bachelor’s, master’s, or PhD in Computer Science, Electrical/Electronics Engineering, Engineering, or related field.
About the job
Leads cross-functional execution of rack-scale AI data center hardware programs from concept through production, covering system integration, validation, milestones, risks, and issue resolution.
What you'll do
- Own integration plans and coordinate hardware, firmware, software, manufacturing, and validation work across rack-scale systems.
- Lead design and readiness reviews, platform debug, issue triage, and corrective actions through verified closure.
- Manage schedules, requirements, deliverables, risks, KPIs, and stakeholder communications.
What they ask for
- Bachelor’s degree in a related field and 6+ years of Hardware Engineering or related work experience; OR master’s degree and 5+ years; OR PhD and 4+ years.
- Experience in systems or hardware engineering, hardware project lifecycle management, and technical product/program management.
- Experience managing technical programs across cross-functional teams and coordinating release schedules.
- Experience with server technologies, including board design, SIPI, thermal and mechanical aspects, BIOS, BMC, and networking.
Nice to have
- Experience with rack level systems and components.
- Master’s degree in computer science/engineering, electrical engineering, or a related field.
Pay
$169,800.00 - $254,600.00 (base salary)
Tools
PCIe, BIOS, BMC, Redfish, SharePoint, JIRA/Confluence, Microsoft Office, Agile
AI focus
Leads hardware and validation engineering for rack-level AI inference solutions in liquid-cooled data centers.
Model-written summary · the original posting is authoritative