Software Engineer, Data Engineer

CEO & Co-Founder | Revolutionizing the Energy Development Process

Staff Software Engineer (Applied AI & Data Workflows)

Location: Salt Lake City, Utah (In-Office, Full-Time; relocation support available)
Reports to: Head of Engineering, US

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Grid is a well-funded startup building a next-generation SaaS platform to accelerate the development of modern, low-cost power plants and AI infrastructure, including data centers, solar, wind, battery storage, nuclear, and transmission.

Energy is the world's largest and most critical industry, and it's undergoing a once-in-a-century transformation driven by rapid AI datacenter expansion. Our AI-powered platform is built to meet this moment. By transforming fragmented data, manual workflows, and institutional knowledge into a single intelligent work orchestration system, we help energy and data center developers move faster, reduce costs, and make better decisions.

Our product strategy is intentionally broad and ambitious, supporting users across multiple domains: land control, interconnection, permitting, engineering, finance, stakeholder engagement, and more.

We are looking for a Staff Software Engineer who combines deep technical expertise with strong product instincts and a track record of owning systems that materially moved key business metrics.

You will be a senior technical leader on the team, responsible for designing and delivering data-heavy, workflow-oriented software with applied AI at its core. You'll work closely with teammates in the US and India to architect systems, ship end-to-end features, set engineering standards, and mentor other engineers as we build our MVP and beyond.

This role is ideal for someone who:

• Has 5–10 years of experience building and scaling complex software systems.
• Has owned a major product or platform build that contributed directly to company success (e.g., revenue growth, new product line, major efficiency gains).
• Is excited to work in-person with the founding team in Salt Lake City and help shape both the product and the engineering culture from an early stage.

• Lead design and implementation of core platform services, data models, and workflow engines.
• Make architecture decisions that balance speed, reliability, and long-term scalability.
• Define and advocate for engineering best practices across code quality, testing, observability, and security.
• Apply strong systems fundamentals (concurrency, transactions, indexing, caching, consistency) to ensure correctness and performance across data flows, documents, and geospatial workflows.
• Build operationally excellent services with proper observability, monitoring, alerting, and performance tuning for both real-time and batch data movement.
• Collaborate with AI experts to integrate LLMs, vector search, and orchestration tools into customer workflows that deliver genuine value.

• Own features from idea to production: scoping, design, implementation, code review, deployment, and iteration.
• Partner with Product and Design to translate customer needs into elegant, performant user experiences.
• Work across the stack as needed (data, backend, and collaborating closely with frontend).
• Serve as a technical mentor and thought partner to other engineers.
• Help establish a high-ownership, low-ego, collaborative engineering culture.
• Contribute to hiring, onboarding, and shaping our engineering processes as we scale.

• Engage directly with customers and early lighthouse users to understand workflows and validate assumptions.
• Use data and feedback to prioritize work that moves key product, customer, and business metrics.

• 5–10 years of professional software engineering experience
  , with significant time spent on complex, data-heavy enterprise or workflow SaaS products.
• Demonstrated ownership of at least one major system or product area that drove clear business impact (e.g., new product launch, major workflow automation, significant revenue or adoption lift).
• Strong experience building data-centric applications
  , including:
• Relational + No
  
  SQL databases
• Data modeling, indexing, and performance…