System Integration Manager

Location: Mountain View/San Jose Bay Area

Team: System Engineering

The Impact You’ll Make

The System Integration Manager owns the end-to-end integration of power electronics subsystems — inverters, DC/DC converters, battery management systems, controllers, and protection equipment — into complete, field-ready renewable energy systems. This role sits at the intersection of electrical, hardware, controls, mechanical, and software engineering, translating subsystem-level designs into a system that works reliably together, passes certification, and performs in the field. The ideal candidate has hands-on experience bringing power electronics hardware through system-level validation, and is comfortable being the person who catches integration problems before they become field failures.

Key Responsibilities

System Architecture & Integration

Own the system-level integration across power electronics, battery, controls, and mechanical/thermal subsystems for BESS and PV/hybrid products.
Define interface control documents between subsystem teams — electrical interconnects, communication protocols (CAN, Modbus, RS-485), control signal timing, and grounding/bonding schemes.
Identify and resolve cross-domain design conflicts (e.g., thermal derating impacts on power electronics placement, EMI/EMC interactions between converters and BMS communication).
Lead root-cause investigations when subsystems that pass individual qualification fail at system level.

Verification & Validation

Develop and execute system-level test plans: power-up sequencing, fault injection, grid-fault ride-through, protection coordination, and communication/control loop validation.
Coordinate factory acceptance testing (FAT) and site acceptance testing (SAT) for containerized BESS and PV systems.
Work with the safety/certification team to ensure system designs support UL 9540, UL 9540A, UL 1741, and UL 1973 pathways, and that integration choices don't compromise certification scope.
Maintain traceability between requirements, interface specs, and test evidence for design reviews and customer/lender due diligence.

Cross-Functional Leadership

Act as the technical integration point of contact across mechanical/thermal, electrical/power electronics, BMS/firmware, and safety/certification teams.
Support new product introduction (NPI) by flagging integration risk early in the design cycle, not just at system test.
Mentor integration engineers and test technicians; build out test infrastructure and documentation standards as the team scales.

The Skills You Bring

Degree in Electrical Engineering, Controls, or equivalent experience with a focus on Power Systems, Control Theory, and software-defined controls.
5+ years of experience building EMS, PPC, or plant-level controls for utility-scale solar, storage, hybrid, or wind power plants.
Deep working knowledge of utility and industrial communication protocols: DNP3, IEC 61850, Modbus TCP/RTU, SunSpec, MESA-ESS, IEEE 2030.5, OPC UA, CAN — including hands-on protocol mapping, point list design, and debugging (Wireshark, protocol analyzers, simulators).
Hands-on experience with SEL RTAC, Codesys, and MATLAB / Simulink for model-based control development. Experience with industrial HMIs and historians (Ignition, AVEVA/Wonderware, Canary, OSIsoft PI) is a strong plus.
Strong understanding of grid-following and grid-forming inverter control, droop response, virtual inertia, and the trade-offs between them at plant scale.
Familiarity with IEEE 1547-2018, IEEE 2800, UL 1741 SB/SC, IEEE 519, FERC Order 2023, and applicable NERC reliability standards.
Proven ability to author concept of operations documents, sequence diagrams, state machines, and control narratives that engineering, operations, and external stakeholders can all build against.
Proficiency in Python (or similar) for tooling, point list automation, and SCADA data analysis.
Fluency with AI-assisted development — daily use of LLM coding assistants and agentic workflows to accelerate control code, test harnesses, point list generation, protocol parsing, and documentation. Working knowledge of applying ML/AI to operational data (forecasting, anomaly detection, optimization) is a strong plus.