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VP of Software Engineering
Not specifiedFull-timeEngineering ManagementSemiconductorsData Center Infrastructure
Lead the software stack and engineering organization for high-efficiency AI inference workloads in data centers. This is a hands-on executive role spanning silicon-adjacent development, AI software infrastructure, and early customer releases.
Responsibilities
- Own architecture and delivery of the software stack for AI inference workloads in data centers.
- Lead firmware, Linux kernel driver, memory management, and hardware-software co-design work for emerging ASIC, CPU, and GPU architectures.
- Build compiler paths and runtime engines that efficiently execute complex AI models on target hardware.
- Design software abstraction, virtualization, clustering, scheduling, and orchestration for distributed data center infrastructure.
- Recruit, mentor, and manage an engineering team across embedded systems, compilers, and infrastructure.
- Work with silicon and hardware teams to benchmark real-world workloads, identify bottlenecks, and inform chip revisions.
- Establish rapid software development processes and guide products from proof of concept and chip bring-up through alpha and beta releases.
- Provide APIs and framework integrations that enable enterprise data center customers to run workloads on the hardware.
Requirements
- 10+ years of software engineering experience, including leadership as a VP of Engineering, VP of R&D, or Head of Software.
- Experience leading high-performing, multi-layered engineering organizations.
- Experience in early-stage startups or hardware bring-up, combining strategic architecture with hands-on technical work.
- Deep understanding of data center compute workloads, distributed systems, and infrastructure for high-density AI inference.
- Experience with low-level development, kernel drivers, memory layout, and semiconductor ecosystems such as ARM or custom compute architectures.
- Experience building or managing teams working on deep learning compilers, model optimization, and high-throughput execution engines.
- Ability to turn business milestones into focused software roadmaps and prioritize time-to-market and performance.