Qualcomm
Hexagon and RISC-V Software Product Manager
$182K–$273K
San Diego, California · On-site · Manager · Full-time · Posted Sep 17, 2026
- Experience
- 5+ years of Product Management or related work experience; relevant experience in engineering, applications engineering, or product management is also requested, with no years specified.
- Education
- Bachelor's degree in Engineering, Information Systems, Computer Science, Humanities, or related field.
About the job
Leads product strategy and execution for Qualcomm’s Hexagon and RISC-V embedded software products, with a focus on developer platforms, ecosystem growth, and customer adoption.
What you'll do
- Define product strategy and roadmaps based on market needs, customer feedback, and competitive analysis.
- Improve developer experience across toolchains, SDKs, RTOS integration, and system software; lead engagement in open-source ecosystems.
- Coordinate launches and ongoing improvements with engineering, marketing, customer support, and customers; drive developer adoption and design wins.
What they ask for
- Expertise in embedded processor architectures and software, including strong understanding of microcontrollers and DSP architectures and deep experience with at least one major architecture such as ARM or RISC-V.
- Understanding of embedded software and RTOS principles, with hands-on experience using compilers, debuggers, profilers, emulators, and other embedded development tools.
- Bachelor's degree in Engineering, Information Systems, Computer Science, Humanities, or a related field.
- Excellent verbal and written communication skills, including conveying technical concepts to executive and non-technical stakeholders.
Nice to have
- Experience with open-source development.
- Familiarity with FreeRTOS, Zephyr, Qualcomm RTOS (QuRT), or similar RTOS; embedded development workflows or middleware.
Pay
$181,800.00 - $272,600.00 (base salary)
Tools
Hexagon, RISC-V, ARM, C/C++, FreeRTOS, Zephyr, Qualcomm RTOS (QuRT), SDKs
AI focus
Strengthen Qualcomm’s position in edge AI and support AI workloads on embedded software platforms.
Model-written summary · the original posting is authoritative