This position is based in our San Francisco office and operates on an onsite work model.
Essential Duties and Responsibilities
Multi-Level SIL & HIL Validation Architecture
Power Electronics & Site-Level Simulation: Direct the architecture and scaling of our Software-in-the-Loop (SIL) and Hardware-in-the-Loop (HIL) infrastructure (Typhoon HIL, Opal-RT) across both sub-microsecond power conversion stages and multi-asset, site-level controllers.
Custom HIL Hardware & Plant Modeling: Oversee the design of custom signal-conditioning interface hardware, fault-injection panels, and high-fidelity virtual plant models (battery arrays, resonant DC/DC and multi-level AC/DC converters, and dynamic grid conditions) to stress-test embedded firmware and site software before field deployment.
Continuous Verification & CI/CD: Integrate automated SIL and HIL regression suites into containerized CI/CD pipelines (GitHub Actions/Jenkins, Docker), serving as the definitive release gate for all production-bound embedded Rust, C/C++, and site-level software.
Manufacturing Software & Factory Test
Production Line Software: Lead the development of automated manufacturing test software and end-of-line (EOL) functional test frameworks for multiple Redwood hardware product lines, including our custom Power Conversion Systems (PCS) and energy storage enclosures.
Factory-to-Engineering Integration: Build reliable firmware flashing, hardware calibration, serialization, and automated pass/fail diagnostics systems that scale from low-volume prototype builds (EVT/DVT) to high-volume factory production.
Site Commissioning & Predictive Fleet Analytics
Commissioning Tooling: Architect and deliver intuitive, automated field commissioning tools that streamline site bring-up, verify hardware-software wiring and communications (CAN, Modbus TCP, Ethernet, SPI), and execute automated site acceptance testing (SAT) for new energy storage deployments.
Preventive & Predictive Maintenance Analytics: Lead the architecture of fleet-wide data analytics frameworks and time-series observability pipelines (e.g., InfluxDB, Prometheus, Grafana, Python) that ingest continuous telemetry from deployed field assets to drive preventive and predictive maintenance.
Prognostics & Early Fault Detection: Develop automated health-monitoring models and anomaly detection algorithms that track thermal drift, component degradation, switching efficiency shifts, and battery state-of-health (SoH) trends—flagging incipient hardware or control issues for proactive servicing before they cause unplanned downtime.
Leadership & Organization Building
Team Growth & Technical Mentorship: Recruit, mentor, and lead a multidisciplinary team of validation, test automation, manufacturing software, and data/reliability engineers; foster an engineering culture obsessed with breaking complex state machines and catching failure modes early.
Cross-Functional Execution: Partner closely with Power Electronics Controls, Embedded Firmware, Hardware Engineering, Manufacturing Operations, and Field Service teams to close the loop between factory test signatures, HIL models, and real-world predictive maintenance actions.
Skills, Knowledge, and Abilities
Qualifications
Education & Experience: MS or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field (or BS with equivalent elite depth), combined with 10+ years of industry experience in software validation, HIL simulation, manufacturing test, and fleet reliability analytics for complex hardware systems, and 5+ years leading technical engineering teams.
SIL/HIL & Power Systems Mastery: Proven track record architecting real-time simulation environments (Typhoon HIL, Opal-RT, or dSPACE) for both high-frequency power electronics converters and distributed system/site controllers.
Manufacturing & Commissioning Software: Demonstrated experience building and deploying automated factory test software (ICT/FCT/EOL), hardware bring-up utilities, and field commissioning frameworks across multiple hardware product lifecycles.
Predictive Analytics & Software Toolchain: Expert-level proficiency in Python (Pytest, Pandas, SciPy, time-series and predictive modeling stacks) for test automation and fleet prognostics, alongside solid working fluency in Rust and C/C++ to inspect, instrument, and debug low-level firmware and application codebases.
Data Infrastructure & DevOps: Strong experience designing automated CI/CD pipelines for hardware-in-the-loop targets, containerization (Docker), and scalable time-series telemetry architectures for fleet health monitoring and predictive maintenance.
Hardware & Lab Fluency: Deep comfort operating in high-voltage power electronics lab environments, utilizing oscilloscopes, logic analyzers, power analyzers, and industrial communication protocols (CAN/CAN-FD, Ethernet, Modbus, SPI) to isolate elusive hardware-software interactions.
Bonus Qualifications
Experience validating grid-scale Battery Energy Storage Systems (BESS), utility-interactive inverters, or mixed-chemistry/second-life EV battery installations against UL 1741, UL 1973, and IEEE 1547 standards.
Proven experience building prognostic algorithms that correlate factory EOL baseline signatures with in-field operational telemetry to predict remaining useful life (RUL) of power electronics or energy storage components.
Track record of designing custom automated fault-injection hardware and custom breakout PCB interfaces for multi-rack HIL testbeds.
In accordance with California pay transparency laws, the salary range for this position is listed below. Actual compensation may vary based on a variety of factors, including experience, education, and skills.
California Pay Range
$220,000—$347,500 USD
The position is full-time. Compensation will be commensurate with experience.
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