Application Guide

How to Apply for Senior Software Engineer, Platform

at Gridmatic

🏢 About Gridmatic

Gridmatic is uniquely positioned at the intersection of clean energy, data science, and real-time grid operations, using machine learning to optimize battery assets and power markets. Their mission-driven focus on accelerating the clean energy transition makes them appealing to engineers who want their technical work to have direct environmental impact. As a remote-first company working on critical infrastructure, they offer the chance to solve complex reliability challenges that affect both revenue and grid stability.

About This Role

This Senior Software Engineer role focuses on building and scaling Gridmatic's compute platform to support production services, batch jobs, and ML training workloads on GCP. You'll be responsible for designing real-time systems for battery asset operations where reliability directly impacts financial outcomes and grid stability. The role involves establishing patterns, tooling, and best practices that enable teams across the company to run services reliably as they grow.

💡 A Day in the Life

A typical day might involve designing Terraform modules for new GCP services, debugging Kubernetes cluster issues affecting real-time battery operations, collaborating with ML engineers to optimize training workloads on GKE, and establishing reliability patterns that teams across Gridmatic will use. You'll balance immediate platform reliability needs with architectural decisions that shape how the company builds software as it scales.

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Interview Prep

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🎯 Who Gridmatic Is Looking For

  • Has 5+ years experience building production infrastructure on GCP (or AWS/Azure with ability to translate to GCP), with deep hands-on Kubernetes expertise (specifically GKE experience is ideal)
  • Proficient in Python for platform tooling and automation, plus either Go experience or strong systems programming background in C++, Java, or Rust
  • Has implemented infrastructure-as-code at scale using Terraform and understands how to balance reliability requirements with development velocity
  • Thrives in environments where platform decisions directly impact both business revenue and critical infrastructure reliability

📝 Tips for Applying to Gridmatic

1

Highlight specific GCP or multi-cloud migration experience, especially if you've worked with GKE - mention cluster scaling, networking, or cost optimization projects

2

Demonstrate how you've improved reliability in previous roles, particularly for systems where downtime had financial consequences

3

Show Python proficiency through concrete examples of platform tooling or automation you've built, not just data science scripts

4

If you lack Go experience, emphasize your systems programming background in C++, Java, or Rust with examples of performance-critical code

5

Connect your experience to clean energy or infrastructure reliability themes, showing understanding of Gridmatic's dual mission of profitability and grid impact

✉️ What to Emphasize in Your Cover Letter

["Your experience with Kubernetes in production environments, specifically how you've solved reliability challenges for critical systems", 'Examples of infrastructure-as-code implementations using Terraform that improved team productivity or system reliability', "How your background aligns with Gridmatic's mission of clean energy transition through technical infrastructure", "Specific contributions you've made to platform architecture decisions that helped engineering teams scale effectively"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Gridmatic's battery optimization products and how they interact with power markets (CAISO, ERCOT, etc.)
  • → The company's recent funding rounds and growth trajectory to understand their scaling challenges
  • → Their tech blog or engineering presentations to understand current platform architecture
  • → Clean energy market dynamics and how software impacts battery revenue optimization

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Designing Kubernetes-based platforms for mixed workloads (real-time services, batch jobs, ML training) on GCP
2 Implementing reliability patterns for systems where downtime has direct financial impact
3 Terraform module design and state management strategies for growing infrastructure
4 Performance optimization of Python-based platform services and potential migration to Go
5 Balancing rapid feature development with infrastructure stability in a scaling startup environment
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⚠️ Common Mistakes to Avoid

  • Focusing only on AWS/Azure experience without demonstrating ability to translate concepts to GCP
  • Treating Kubernetes as just a deployment tool rather than a core platform component requiring deep operational knowledge
  • Presenting Python experience limited to data science/ML without showing systems programming or platform development examples

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Gridmatic!

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