Jobs Companies Camus Energy Power Systems Software Engineer

Sobre esta vaga de Power Systems Software Engineer na Camus Energy

Camus Energy · Remote

About Us

Camus Energy builds software solutions that help new load and generation connect to the grid faster—without sacrificing reliability.

As electricity demand accelerates and clean energy scales, traditional interconnection processes are becoming the bottleneck. Utilities and developers face growing queues, long timelines, and costly upgrades that slow progress across the grid.

Camus enables flexible grid connections that allow new load and generation to connect sooner by planning for and operating within real system constraints. Our platform bridges the gap between grid operators and large load developers, providing a view of time-varying grid capacity for any given new interconnection point. 

We combine high-reliability software experience from companies like Google and Meta with deep power systems expertise across the utility sector. If you’re excited to work at the intersection of infrastructure, software, and climate, we’d love to hear from you.

The Role

We're looking for a Power Systems Software Engineer to own and advance the power systems modeling capabilities at the heart of the Camus platform. This is an individual contributor role with real technical depth and product influence; you'll be responsible for the full stack of power systems work, from developing and validating high-fidelity models to driving the architecture that makes these models run reliably at scale.

This is not a role where the product requirements are handed to you. You will work directly with utility customers to understand their data and validate model outputs against real system measurements, bringing that ground-truth perspective back into product decisions. You'll also work closely within the Engineering team to deploy power flow models in our cloud-native architecture, and unlock large-scale planning studies and real-time orchestration of DERs. 

The problems we're solving don't have off-the-shelf answers. We work as a tight, technical team that moves with urgency but builds with the discipline that production-grade software demands. If you want to do the most technically interesting power systems modeling work in the industry while directly shaping how it becomes a product, this is the role.

What You'll Do

  • Develop and maintain high-fidelity power flow & optimal power flow models
  • Write and maintain automated tests and validation pipelines that verify model accuracy, catch regressions and ensure solver reliability
  • Drive the architecture of solvers that balance accuracy with computational performance 
  • Build tooling that visualizes and translates model outputs into actionable insights, for internal and client-facing applications 
  • Partner with our utility customers to understand their datasets and validate model outputs against their system measurements 
  • Collaborate with Camus’ internal teams to integrate utility models (GIS, ADMS, and time series data) into the Camus platform
  • Identify and resolve computational bottlenecks in large-scale grid simulations

What You'll Bring

  • Masters/Ph.D. in Electrical Engineering, Computer Science, or related discipline with 5+ years of industry experience deploying power systems models for real world applications
  • Strong foundations in power systems concepts, methods and convex/non-convex optimization solvers for distribution grids
  • Experience working with large utility datasets (GIS, SCADA, AMI, network models)
  • Experience with OpenDSS or other open source or commercial power flow modeling software
  • Ability to translate complex mathematical formulations into production-ready code
  • Strong Python skills: you write clean, maintainable, production-ready code, not just analysis scripts
  • Excellent problem-solving, communication, and collaboration skills
  • Comfortable operating with autonomy in a small team, balancing speed of delivery with the engineering discipline that production-grade software demands.

Nice to Have

  • Experience with hosting capacity and interconnection studies
  • Experience with transmission grid planning or operations software
  • Experience with time-series forecasting, or other AI applications in grid analytics
  • Experience with GCP or other cloud platforms 
  • Able to leverage AI code development tools to accelerate development.

What We Offer

  • Competitive base salary
  • Comprehensive benefits, including FSA and 401k for full time employees
  • Fully remote workplace with options for in office work in the Bay Area
  • Flexible PTO, which we encourage you to use!
  • A real impact on climate change - we’re building the world we want to live in and we want you to join us!

The expected base salary for this role is $180,000 - $230,000 annually, depending on experience, skills, and qualifications.

 

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Como este salário de Software Engineer se compara

Esta vaga paga $205,000/yrem linha com da faixa típica para vagas de Software Engineer.

$102,394 a mediana $183,150 $251,000

Faixa típica $150,000–$220,000/yr, com base em 1,350 vagas de Software Engineer comparáveis na JobsRadar (pagamento anualizado em USD). Ver insights salariais de Software Engineer →

Sobre a Camus Energy

Camus Energy was founded in 2019 in the San Francisco Bay area. We have deep experience designing and operating distributed systems, and a passion for combating climate change. From pioneering work at Google, SpaceX, and Uber, we bring expertise in massively parallel cloud computing, high-scale real-time analytics, and high-reliability computing. We work on building software for the grid. The challenges faced by grid operators in an evolving energy landscape are unique. The existing grid is one of humanity’s largest machines, and keeping it running safely and smoothly is critical to modern life. As it becomes smarter, more connected, and more dynamic, we are leveraging the pioneering efforts and innovation from other industries to manage the challenges of scale and reliability for an effective energy transition.

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