CAD & Engineering Infrastructure Lead
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
Build and own the engineering platform behind silicon development, including compute infrastructure, EDA ecosystems, integrated RTL-to-GDS release flows, CI/CD pipelines, tool deployment, licensing, and AI-assisted workflows.
Requirements
- Deep understanding of the ASIC development lifecycle from architecture and RTL through tapeout.
- Experience owning CAD and infrastructure across multiple successful SoC programs.
- Hands-on experience setting up and maintaining integrated RTL-to-GDS flow environments.
- Experience with tool and version management, foundry and IP collateral integration, and flow release qualification.
- Strong understanding of distributed scheduling, storage, networking, cloud environments, and license management.
- Hands-on experience with Synopsys, Cadence, and Siemens EDA ecosystems.
- Knowledge of version control, CI/CD platforms, and high-volume regression workloads.
- Excellent scripting and automation skills using Python, Tcl, Bash, or similar.
- Experience evaluating and deploying AI-assisted engineering tools and workflows.
- Experience scaling infrastructure in an early-stage semiconductor company.
- Experience with advanced technology nodes, agentic AI systems, LLM-based tooling, chiplets, or advanced packaging.
Responsibilities
- Define engineering infrastructure requirements for compute, storage, scheduling, security, backup, disaster recovery, and cloud.
- Lead AI adoption across engineering functions and standardize AI-assisted workflows.
- Own design-flow CI/CD pipelines, flow-release qualification, and result dashboards.
- Provide compute, capacity, and deployment support for high-volume regressions.
- Assemble, regression-test, version, deploy, and roll back qualified flow releases.
- Lead deployment and integration of multi-vendor EDA tools.
- Own EDA licensing strategy, vendor relationships, procurement, budgets, IP administration, and compliance.
- Build and operate the platform for AI-assisted engineering.
- Measure AI productivity impact and protect proprietary design data.
Benefits
- Performance-based incentives
- Equity participation
- Medical coverage
- Dental coverage
- Vision coverage
- Paid time off
- Flexible work arrangements
- Professional development opportunities
