Power Management Architect
Velaura
Power Management Architect
Velaura
Designs energy-efficient AI silicon and systems
Salary Range: 200000 to 300000 (Currency: USD) (Pay period: per-year-salary)
Velaura is designing the compute silicon that powers robots, autonomous systems, and intelligent machines that operate in the physical world—where energy is scarce, thermal headroom is limited, and every milliwatt affects range, runtime, and performance. As Power Management Architect for our Physical AI System-on-Chip (SoC), you will own the power architecture of our silicon: defining how the chip delivers, distributes, and manages energy across compute, AI/NPU, memory, and I/O so that our platforms hit their performance targets within tight power and thermal budgets.
This is a foundational, cross-cutting role spanning silicon, firmware, platform software, and product teams. You will set Velaura’s power management strategy from the earliest architecture phase through tape-out and production—shaping power delivery, voltage and frequency scaling, low-power states, and the hardware/software control that keeps Physical AI systems efficient in the field.
Own the SoC power architecture: define power domains, voltage/frequency (DVFS) strategy, power states, and the power delivery network across Velaura’s Physical AI silicon roadmap.
Define dynamic and static power management techniques including clock and power gating, adaptive voltage scaling, body biasing, and retention strategies, to maximize performance-per-watt for AI and real-time workloads.
Establish power and energy budgets and model them across use cases; drive power, performance, and area (PPA) trade-offs with architecture, design, and product teams.
Architect the on-die power management and control subsystem—PMIC interface, power management controller, sensors, and telemetry—and the firmware/software policies that drive it.
Partner with silicon design, firmware, thermal, package, and platform software teams to embed power intent (e.g., UPF) into the design flow and validate it through implementation and silicon bring-up.
Define power and thermal management for sustained real-world operation, including thermal throttling, energy-aware scheduling, and safe operating limits.
Establish power architecture standards, modeling methodology, and review practices; mentor engineers and raise the power-engineering bar across the organization.
8+ years in power management, mixed-signal, or SoC architecture, with significant experience defining power architecture for shipping silicon or embedded platforms.
Deep expertise in low-power design techniques: multiple power domains, DVFS, clock/power gating, adaptive voltage scaling, retention, and power state management.
Strong understanding of power delivery networks, PMICs, voltage regulation, and the interaction between power, thermal, and package constraints.
Hands-on experience with power intent and low-power methodology (e.g., UPF/CPF) and with power modeling and analysis across the SoC design flow.
Experience working across silicon design, firmware, and platform software to define and validate power management policies from architecture through silicon bring-up.
Bachelor’s or advanced degree in Electrical/Computer Engineering or a related field, or equivalent practical experience.
Excellent written and verbal communication skills, with a track record of influencing technical direction and mentoring engineers.
Experience optimizing power for AI/ML accelerators or NPUs and for real-time or latency-sensitive edge workloads.
Familiarity with robotics, automotive, mobile, or other power- and thermally-constrained domains, and with battery and energy-storage considerations.
Experience with energy-aware software/firmware, thermal management, and silicon power characterization and correlation.
Prior experience at an early-stage or high-growth semiconductor or hardware company, building power architecture and methodology from the ground up.
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.
Velaura AI designs and manufactures ultra-energy-efficient AI infrastructure, including 3nm ASIC chips, Teraflux mining systems, FluxVision fleet-management software, and AuraLinks rack-level networking. Customers deploy the hardware in data centers, while FluxVision monitors and manages fleets; EnergyTune and AutoTune dynamically adjust power to meet grid stability, and AuraLinks reduces bottlenecks in AI training and inference. The company differentiates itself with a team of silicon architects from Apple, Google, and Qualcomm, plus a patent-pending energy-management approach and a fully integrated hardware-software stack. Its goal is to enable massive AI deployment by delivering powerful, energy-efficient compute and networking that aligns with sustainable energy grids and domestically produced technology.
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