Principal AI SoC Runtime Software Architect
Velaura AI develops ultra-low-power silicon and software technologies for AI compute infrastructure. Its solutions serve hyperscale data centers and Physical AI applications such as robotics, autonomous systems, drones, and edge devices.
Maintainer signals as of 8/23/2026
Funding history
About Velaura AI, Inc.
Velaura AI is an AI compute infrastructure company developing ultra-low-power silicon and software technologies. Its Titan Core™ platform uses proprietary digital chip IP, low-voltage libraries, EDA flows, and design methodologies to improve performance per watt in AI accelerators while maintaining performance, yield, and reliability. The company also applies this technology to Physical AI systems, including industrial robots, autonomous machines, drones, humanoids, and edge devices. Velaura engages hyperscalers, XPU companies, and developers of next-generation AI infrastructure and Physical AI solutions.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Own the software architecture for a heterogeneous AI SoC and define the end-to-end runtime across sensor ingest, preprocessing, AI inference, postprocessing, and application delivery. Coordinate workloads and data movement across CPU cores, AI accelerators, vision and multimedia engines, and embedded processors while establishing memory-sharing, synchronization, API, observability, resilience, and recovery architectures.
Requirements
- Extensive experience designing and building production runtime systems, embedded middleware, multimedia frameworks, or performance-critical systems software.
- Strong C/C++ programming skills and experience architecting production runtime software across APIs, libraries, drivers, firmware, and hardware interfaces.
- Understanding of heterogeneous and asynchronous execution, synchronization, concurrency, scheduling, and resource management.
- Understanding of device memory, DMA, IOMMU/SMMU, cache coherency, memory mapping, shared buffers, and kernel/user-space memory interfaces.
- Experience optimizing data movement and execution across multiple hardware engines.
- Experience designing stable runtime APIs with compatibility, versioning, error handling, diagnostics, and recovery behavior.
- Ability to debug cross-layer correctness and performance problems using profiling and tracing.
- Technical leadership across component and organizational boundaries.
- Preferred experience includes AI inference runtimes, Linux kernel development, robotics, edge AI, camera pipelines, GStreamer, compiled-model artifacts, and embedded Linux SDKs.
Responsibilities
- Define the SoC-wide execution model for coordinating workloads across heterogeneous compute and media engines.
- Set the architecture and technical direction for the AI inference runtime.
- Own the end-to-end dataflow architecture for sensor-to-application pipelines.
- Define the SoC-wide memory and buffer-sharing architecture across user space, the kernel, and hardware engines.
- Define interface contracts among the runtime, kernel drivers, firmware, and hardware engines.
- Partner with the compiler team to define the compiler-runtime contract.
- Establish system-wide observability and performance architecture.
- Define runtime resilience and validation architecture.
Benefits
- Medical coverage
- Dental coverage
- Vision coverage
- Paid time off
- Flexible work arrangements
- Professional development opportunities
- Performance-based incentives
- Equity participation