Senior / Staff Software Engineer, Full Stack Software Products

The company delivers affordable, reliable energy to industry, data centers, and the grid. Our thermal batteries turn low-cost electricity into always-on heat and power, without supply-constrained critical minerals or multi-year construction timelines.

We are growing our company with people who put team and mission first, value connection through laughter and joy, and work with humility and openness. We are committed to building a diverse, passionate, and creative team dedicated to a future powered by abundant, clean, low-cost energy.

About The Role

The company is looking for a full-stack product engineer to build the software products that power our business - from external customer experiences to internal tools used by teams across Business Development, Operations, and R&D.

In this role, you’ll help shape product vision, design the underlying data models, and connect AI systems with the business logic that makes them useful. You’ll own products end to end, working directly with users to understand their workflows, translate ambiguous needs into practical solutions, and ship software that performs reliably in production.

You’ll also help build the company’s long-term software capabilities. That means creating systems, standards, and guardrails that allow partner teams to safely modify existing tools and build new ones within our ecosystem - without engineering becoming a bottleneck.

This is a highly autonomous role with direct influence over how software is designed and built at the company. We’re looking for deep expertise in one or more core areas - such as software engineering, data modeling, AI integration, or product development - along with the curiosity and practical judgment to work across the full stack.

What You'll Do

Build Full-Stack Products

Design, build, deploy, and maintain internal and external software products across the frontend, backend, data, and AI layers. Own the complete product lifecycle, including architecture, observability, reliability, and ongoing maintenance.

Enable Self-Service

Put workflow creation directly into users’ hands. Build systems that allow analysts, operators, and other domain experts to adapt their own tools without filing a ticket and waiting for engineering support.

Co-Create with Users

Work alongside the people doing the work. Learn their processes, build solutions with them, and give them the tools and confidence to continue improving those solutions independently.

When users contribute their own code or workflows, you’ll make those contributions safe to run, easy to review, and straightforward to maintain.

Establish a Unified Data Model

Design the data foundation that powers the company’s products. Connect business systems, operational data, and plant telemetry through tested transformation pipelines and a governed semantic layer.

You’ll help ensure that critical concepts—such as revenue, availability, and delivered steam—have consistent definitions across dashboards, AI assistants, applications, and autonomous agents.

Design for Data Security

Build and enforce strong access controls for sensitive, proprietary, and counterparty-restricted data. Ensure every product, workflow, and AI interface consistently respects authorization boundaries.

At the company, an AI system that answers an unauthorized question is not a clever feature—it is a business risk.

Build Proactive AI Guardrails

Make evaluation a core part of product development rather than a final checkpoint. Create systems that identify task failures, tool-calling errors, grounding gaps, security issues, and regressions before they reach users.

Where AI systems influence financial decisions, operational dispatch, or customer commitments, you’ll build safeguards that are rigorous, reliable, and easy for teams to use.

Set Engineering Standards

Help define architectural patterns, development practices, and technical guardrails across the company’s software ecosystem. Distinguish between controls that prevent real failures and processes that create unnecessary friction.

What We're Looking For

• Strong product judgment. You can turn vague, shifting requests into a clear product direction, write an effective specification, and ship a solution. You know how to challenge a feature request that misses the underlying problem while maintaining stakeholder trust.

• Production software engineering experience. You have strong Python and TypeScript skills and are comfortable working across frontend and backend systems. You have owned applications end to end, including deployment, observability, reliability, and maintenance.

• Experience shipping AI-powered products. You have built and deployed LLM-powered systems used by real users - and have learned from the unexpected ways those systems failed in production.

• Strong data fundamentals. You are comfortable with SQL, warehouse modeling, and tools such as dbt or equivalent transformation frameworks. You have shipped data changes through CI and think proactively about data quality, freshness, lineage, and testing.

• A collaborative approach to building. You have a track record of building with non-engineers, not simply building for them. You’re comfortable pairing, teaching, reviewing someone’s first pull request, and helping users become increasingly self-sufficient.

• Clear cross-functional communication. You can connect product, data, AI, and software engineering considerations - and communicate technical decisions in a way that allows everyone in the room to contribute.

• Practical risk judgment. You can distinguish between controls that prevent meaningful failures and ceremony that slows teams down. You know where users can safely make changes independently and where review or stronger governance is required.

• A growth mindset. We do not expect one person to be an expert in every discipline. We value deep expertise, intellectual curiosity, sound judgment, and a willingness to learn across the stack.

Bonus Qualifications

• Experience building or maintaining semantic layers using tools such as dbt or Cube

• Familiarity with ClickHouse, time-series data, or IoT systems

• Experience with agent protocols such as MCP or with plugin and tool APIs

• Background in energy, industrial technology, or manufacturing

• Experience managing AI model usage, performance, and cost governance

Work Location: Remote / US based

Salary Range: $183-240k USD

Sala ry Basis

Please note that the salary range listed above reflects the company's estimated pay for this position. The actual salary offered will be within the posted range and determined based on several factors including but not limited to a candidate's experiences, credentials and expertise, as they pertain to the position's requirements.

In addition to a competitive base salary, the company’s Total Rewards program includes equity compensation in the form of stock options, a premium health benefits package with life and disability insurance, a 401K plan with employer contributions, flexible spending accounts, and an industry leading paid-time-off policy that features flexible and inclusive holiday observance, as well as paid volunteer time off.

When it comes to stopping climate change, we need everyone. We believe that having a diversity of backgrounds and experiences strengthens all of us, and we strive to create an environment where every one of us is empowered to create meaningful change.