The posting, in GridCARE's own words
archived Oct 28, 2026About Us
GridCARE is the pioneer of Power Acceleration — a new category solving the most critical constraint in AI's growth trajectory: immediate access to power . As demand for computing skyrockets, access to energy has become the defining bottleneck in the AI infrastructure race. While leading tech companies invest billions in speculative, long-term solutions that may take decades to arrive, GridCARE's Energize™ platform uses physics-based AI to identify and activate gigawatts of hidden capacity in today's electric grid — enabling hyperscalers, data center developers, and utilities to power AI infrastructure years sooner than conventional approaches and without costly upgrades. Founded at Stanford's Doerr School of Sustainability, GridCARE has assembled a world-class team spanning power systems, AI, and infrastructure, and is backed by leading climate-tech and deep-tech investors.
At GridCARE, you will:
⚡ Work at the intersection of AI, energy, and infrastructure — the foundation of the next industrial revolution. 🤝 Partner with hyperscalers, developers, and utilities on high-impact, real-world deployments. 🌎 Help shape a more abundant, efficient, and resilient energy future for the digital era. 🚀 Join a company defining a new category — Power Acceleration for AI. 💰 Receive competitive compensation, equity, and benefits in a fast-growth, mission-driven environment.
Read the full posting ↓
Learn more about GridCARE:
TechCrunch: GridCARE thinks more than 100 GW of data-center capacity is hiding in the grid Utility Dive: Portland General Electric invests in AI-powered flexibility to speed data-center connection GridCARE Raises $64 Million Series A to Create a New Category: Power Acceleration GridCARE Named a World Economic Forum Technology Pioneer for AI Power Innovation
The Role
We're hiring a Senior Distribution Planning Engineer to own GridCARE's distribution planning workstreams. You'll perform distribution power system analyses — power flow studies in CYME and equivalent tools — and build out the planning workflows behind them, aligning distribution results with GridCARE's analyses and platform. You'll have engineering support, but you own the discipline: the methodology, the standards, and execution with utility engagements. Potential to build out a team of distribution engineers as the company and engagements grow.
Responsibilities
Perform distribution and subtransmission power system analyses: power flow, hosting capacity and load-serving studies, contingency and reconfiguration analysis, voltage and thermal limits, and protection considerations. Build out GridCARE's distribution planning workflows end to end — model setup, data intake standards, study criteria, QA, and deliverables. Align distribution analyses with GridCARE's tools, analyses, and platform, including how distribution findings connect to transmission-level work. Assess which flexibility resources can be credited as capacity at the distribution level — batteries, on-site generation, volt/VAR control, feeder reconfiguration. Establish planning criteria, documentation, and validation practices that align with utility distribution planning processes. Partner with Product and AI/ML teams to translate distribution planning methodology into repeatable and scalable platform capability. Lead technical review sessions with utility planners and address utility concerns on data, criteria, and methodology. Travel at least several times a year for in-person utility engagements and conferences.
Qualifications
Required 6-8+ years work experience, including distribution or subtransmission planning. Experience inside a utility distribution planning department. Hands-on ownership of distribution planning studies: power flow, capacity and load forecasting, contingency and reconfiguration analysis, hosting capacity, voltage and protection studies, and capital planning justification. Strong working fluency in CYME or Synergi Working knowledge of DER interconnection standards and state interconnection rules (IEEE 1547, CA Rule 21 or equivalent). Familiarity in Python, and comfort working directly with large, imperfect datasets using power system tool APIs and scientific computing packages (pandas, numpy, etc.). BS in Electrical Engineering.