Velaura is building custom silicon for Physical and Embodied AI, and we are building it
from a blank sheet. The automation our design and verification engineers use to get
from RTL to a clean handoff shapes how fast that silicon comes together.
You will own the front end automation that carries our silicon from RTL entry to a clean
handoff into DFT and implementation. The scope covers RTL design flows, verification
flows from simulation through prototyping, and the AI assisted tooling built over them.
Success is measured two ways. Front end engineers get more done, and the tools they
rely on stay up through every phase of the design cycle.
- Own the RTL design flows including build, lint, CDC and formal checks.
- Own register generation and the generator driven flows behind interfaces and integration.
- Own the DV flows including testbench build, regression execution and coverage collection.
- Own emulation and FPGA prototyping build and bring up.
- Build and deploy AI assisted tooling across design and verification workflows, working with CAD and Engineering Infrastructure on compute and model access.
- Keep these flows available through the design cycle, managing tool versions and turning around bug, upgrade and maintenance requests quickly.
- Measure and improve design and verification productivity, and move proven workflows into standard practice.
- Partner with DFT and physical design on handoff readiness, owning the DFT side flows that sit in the front end.
- 8 or more years in design verification, design or CAD engineering, including ownership of a flow area.
- Strong SystemVerilog and RTL fluency with the ability to read and debug design and testbench code.
- Hands on experience building and running simulation and regression flows including testbench compile, coverage collection and results triage.
- Excellent Python skills and a track record of building tools that other engineers maintain.
- Working knowledge of front end design and verification EDA tools from Synopsys, Cadence or Siemens EDA.
- Working knowledge of Linux administration, distributed compute such as LSF or Slurm, and the storage and scaling constraints behind large regression workloads.
- Familiarity with databases and dashboarding tools such as Grafana for tracking flow health and regression metrics.
- Track record of supporting a live engineering flow with responsive issue turnaround, and the communication skills to work closely with design and verification engineers.
- Experience with UVM, cocotb or Python based verification environments.
- Hands on experience applying LLMs or agentic systems to engineering workflows.
- Experience taking an SoC from RTL bring up through tapeout.
- Experience with emulation and FPGA prototyping platforms such as Palladium, Protium, Veloce or HAPS.
- Experience with retrieval augmented generation, fine tuning or evaluation frameworks for code models.
- Experience at an early stage semiconductor company.
Velaura is building next-generation compute technology for cloud, edge, and Physical AI. Our solutions will enable robots, autonomous systems, drones, and other intelligent machines to operate efficiently in the physical world.
This is an opportunity to help build foundational technology at a time when the industry is undergoing fundamental change. You will work alongside experienced leaders, architects, engineers, and operators who have delivered industry-defining products across mobile, cloud, semiconductor, and AI platforms. If you enjoy solving difficult problems, working across disciplines, and helping shape the future of Physical AI, we would love to hear from you.
Velaura is an Equal Opportunity Employer that is committed to inclusion and diversity. Qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, disability or protected veteran status. We also take affirmative action to offer employment
opportunities to minorities, women, individuals with disabilities, and protected veterans.
Velaura is committed to working with qualified individuals with physical or mental disabilities. Applicants who would like to contact us regarding the accessibility of our website or who need special assistance or a reasonable accommodation for any part of the application or hiring process may contact us at: [email protected]. This contact
information is for accommodation requests only. Evaluation of requests for reasonable accommodation will be determined on a case-by-case basis.
Skills Required
- 8 or more years in design verification, design, or CAD engineering, including ownership of a flow area
- Strong SystemVerilog and RTL fluency, including the ability to read and debug design and testbench code
- Hands-on experience building and running simulation and regression flows, including testbench compilation, coverage collection, and results triage
- Excellent Python skills and experience building maintainable tools used by other engineers
- Working knowledge of front-end design and verification EDA tools from Synopsys, Cadence, or Siemens EDA
- Working knowledge of Linux administration, distributed compute such as LSF or Slurm, and storage and scaling constraints for large regression workloads
- Familiarity with databases and dashboarding tools such as Grafana for tracking flow health and regression metrics
- Experience supporting a live engineering flow with responsive issue turnaround and close communication with design and verification engineers
- Experience with UVM, cocotb, or Python-based verification environments
- Hands-on experience applying LLMs or agentic systems to engineering workflows
- Experience taking an SoC from RTL bring-up through tapeout
- Experience with emulation and FPGA prototyping platforms such as Palladium, Protium, Veloce, or HAPS
- Experience with retrieval-augmented generation, fine-tuning, or evaluation frameworks for code models
- Experience at an early-stage semiconductor company
What We Do
Velaura AI develops ultra-low-power silicon and software for AI compute infrastructure, serving cloud, edge, and physical-AI applications. Its patented, energy-efficient digital-design technology and power-optimized architectures support next-generation AI accelerators, helping compute systems scale with lower energy use. Drawing on deep semiconductor expertise, the company aims to make AI computing more efficient across data centers and intelligent devices, with performance and sustainability central to its approach.
