Qualcomm
Principal SoC Architect, AI Data Center
$217K–$325K
San Diego, California +1 · On-site · Principal · Full-time · Posted Oct 14, 2026
- Location
- San Diego, California
Santa Clara, California - Experience
- 8+ years with a bachelor’s, 7+ years with a master’s, or 6+ years with a PhD; plus 2+ years in a system architecture technology area or product. Preferred: 10+ years of relevant experience.
- Education
- Bachelor’s, Master’s, or PhD in Electrical Engineering, Computer Science, or a related field.
About the job
Leads architecture studies and development of scalable SoCs and data center systems for generative AI inference, from product definition through implementation and production.
What you'll do
- Provide technical leadership for SoC and system architecture studies, specifications, modeling, and implementation guidance.
- Analyze performance, power, area, cost, memory, networking, and scalability tradeoffs; drive performance analysis and closure through production.
- Partner across teams to shape roadmaps, conduct competitive analysis, identify innovations, and mentor technical contributors.
What they ask for
- Bachelor’s degree in Electrical Engineering, Computer Science, or related field and 8+ years of Systems Engineering or related work experience; OR Master’s degree in those fields and 7+ years; OR PhD in those fields and 6+ years.
- 2+ years of experience in one or more system architecture technology areas and products, such as Power System, Shared Resource Management, Limits/Thermal Management, or Hardware Islands.
Nice to have
- 10+ years of relevant experience in SoC, platform, or system architecture; AI accelerators; memory architecture; or memory technologies.
- MS or PhD in EE, ECE, CE, CS, or a related field; relevant architecture expertise and experience leading complex cross-team work.
Pay
$216,600.00 - $325,000.00 (USD, base salary)
Tools
C++, Python, LPDDR, HBM, DDR, GDDR, Ethernet, InfiniBand
AI focus
Architects SoCs and data center systems for generative AI inference workloads; the posting highlights LLM inference, accelerator bottlenecks, and using AI to accelerate workflows.
Model-written summary · the original posting is authoritative