Remote Power Systems Software Engineer: Grid Modeling & Optimization

Camus Energy; Campbell (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Fully remote with Bay Area in-office 0

Flexible PTO

Impactful climate work

Job summary

Camus Energy, Campbell, California, is seeking a Power Systems Software Engineer to own core power systems modeling capabilities within the Camus platform. This role combines high-fidelity modeling with scalable, production‑grade software, working directly with utility customers to validate model outputs against real measurements.

You'll deploy models in a cloud‑native architecture, enabling large‑scale planning studies and real‑time orchestration of DERs, while collaborating with an engineering

Qualifications

• Master's or PhD in Electrical Engineering, CS, or related field.
• 5+ years of industry experience deploying power systems models.
• Experience with large utility datasets (GIS, SCADA, AMI).
• Strong Python production-grade coding.

Responsibilities

• Develop and maintain high‑fidelity power flow & OPF models.
• Write and maintain automated tests and validation pipelines.
• Drive the architecture of solvers balancing accuracy with performance.
• Build tooling to visualize and translate model outputs into insights.
• Partner with utility customers to validate model outputs against measurements.
• Integrate utility models (GIS, ADMS, time series data) into Camus platform.
• Identify and resolve bottlenecks in large-scale grid simulations.

Skills

Power systems modeling

Python programming

OpenDSS

Data analysis

Problem solving

Education

Masters/Ph.D. in Electrical Engineering, Computer Science, or related discipline

Tools

OpenDSS

GCP

Job description

Camus Energy, Campbell, California, is seeking a Power Systems Software Engineer to own core power systems modeling capabilities within the Camus platform. This role combines high-fidelity modeling with scalable, production‑grade software, working directly with utility customers to validate model outputs against real measurements.

You'll deploy models in a cloud‑native architecture, enabling large‑scale planning studies and real‑time orchestration of DERs, while collaborating with an engineering