Senior Site Reliability Engineer

GridCARE is a leading venture-backed startup 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 pioneering physics-based generative AI platform unlocks 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 and backed by leading climate-tech and deep-tech investors, GridCARE has assembled a world-class team spanning power systems, AI, and infrastructure.

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 — capacity acceleration for AI.

💰 Receive competitive compensation, equity, and benefits in a fast-growth, mission-driven environment.

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

• Data Center Dynamics: From Years to Months — Creating an AI Fast Lane for Data Centers

• GridCARE Raises $64 Million Series A to Create a New Category: Power Acceleration

We're looking for a Senior SRE to own the reliability, scalability, and observability of our production systems. You'll work closely with platform and data engineering to keep high-throughput, data-intensive services running at the availability our customers (utilities, data center operators) require.

• Design and operate infrastructure on AWS using Terraform and Kubernetes

• Build monitoring, alerting, and observability (Prometheus, Grafana, Datadog, or similar) with meaningful SLOs/SLIs

• Automate away toil — deployment pipelines, capacity management, self-healing systems

• Partner with engineering on architecture reviews to catch reliability and scalability risks before they ship

• Manage database and data pipeline reliability for large-scale, real-time grid data processing

• Drive security and compliance best practices across infrastructure

Required

• 5+ years in SRE, DevOps, or infrastructure engineering roles

• Deep experience with Kubernetes, Terraform/IaC, and cloud platforms (AWS Preferred)

• Strong scripting/programming ability (Python, Bash)

• Observability Experience (Prometheus, Grafana, Datadog)

• Track record of running on-call for production systems and leading incident response

• Experience with CI/CD pipelines (Github Actions) and infrastructure automation

• Experience with Gitops concepts and tooling (ArgoCD/Flux)

• Solid understanding of networking, distributed systems, and database reliability

• Comfortable operating in a fast-moving startup environment with ambiguity

Preferred

• Experience with data-intensive or real-time processing systems

• Background in energy, climate tech, or critical infrastructure

• Experience scaling infrastructure through hypergrowth

• On-Prem Kubernetes Deployment Experience

• Windows Server Administration Experience

• Competitive salary, performance bonus, and equity.

• Comprehensive health, dental, and vision coverage.

• Lunch provided three days a week in office.

• Hybrid schedule for local employees: 3 days in office for collaboration, 2 days remote for focused work.

• Access to leading academic, industry, and government partners in the AI-energy ecosystem.

• A mission-driven team focused on shaping the future of the energy transition.

$180,000-$230,000 Total

Join us in tackling one of the most important infrastructure challenges of our time — enabling the energy foundation for the age of AI.