Senior Software Engineer

The Team

As part of the Engineering organization, Software Engineering builds the internal platforms and tools that power reactor design, fuel manufacturing, licensing, and plant operations. The team partners directly with engineering, manufacturing, and operations to deliver full-stack software, integrate enterprise systems, and preserve traceability from requirement to as-built.

The Role

The Senior Software Engineer will build the operating system for Valar. You will work directly with reactor and fuel engineers, systems engineering, licensing, manufacturing, supply chain, and operations to understand how they actually work and then build the tooling that makes them faster. This position will be located in Torrance, California, with regular travel to our Orangeville, Utah pilot plant.

Key Responsibilities

• Architect, design, and build full-stack software systems and infrastructure that accelerate reactor design, fuel manufacturing, licensing, and plant operations.
• Build rich, fast web interfaces that engineers, operators, and technicians will use daily—and iterate on them with the people who use them.
• Integrate and extend commercial systems (PLM, ERP, MES, document and records management) using REST and GraphQL APIs, message queues, and event-driven interfaces.
• Develop tooling that eliminates manual document handling and preserves traceability from requirement to as-built.
• Own deployment, observability, and operational health of what you build: CI/CD, infrastructure as code, monitoring, alerting, and on-call for your services.
• Design data models, interfaces, and access boundaries that keep engineering, manufacturing, and quality records consistent, auditable, and usable across teams.
• Diagnose and resolve problems across every layer—client, service, data, deployment, configuration, and network—including in the field during commissioning and startup.
• Use AI coding agents and assistants as a core part of how you work, and review their output with the same rigor you would apply to a human engineer's.
• Lead design and code reviews, set technical direction, and mentor engineers as the software team grows.

Basic Qualifications

• 7+ years of relevant experience writing software and deploying it to a production environment.
• Demonstrated skill in both typed (like Java, C#, Go, or C++) and untyped (like Python or JavaScript) languages.
• Proven experience designing and architecting scalable systems and driving technical decisions across teams.
• Experience building and shipping web applications end to end, including the user interface.
• Working experience with cloud and containerized deployment, infrastructure as code, and CI/CD.
• Solid understanding of computer science fundamentals, including algorithms, data structures, and data modeling.
• Hands-on experience shipping production work with AI coding agents and assistants (Claude Code, Cursor, Copilot, or similar), and the judgment to verify what they produce before it lands.
• Strong communication skills: open to the opinions of others, willing to bring your own creative ideas for solutions, and ready to own and rectify mistakes.
• Bachelor's degree in computer science, engineering, mathematics, or a scientific discipline, or equivalent professional experience.

Preferred Skills and Experience

• Experience building internal platforms or engineering tooling at a hardware, manufacturing, aerospace, energy, or heavy-industrial company.
• Experience integrating PLM, ERP, MES, LIMS, or document control systems, and a healthy skepticism about vendor claims.
• Familiarity with regulated or quality-controlled environments and the software implications of NQA-1, GAMP 5, or 21 CFR Part 11.
• Adjacency to industrial and operational data—historians, time-series stores, OPC UA or MQTT interfaces—and an understanding of why source timestamps and data quality matter.
• Experience with Git, Docker, Kubernetes, and deployment to both cloud and on-premises infrastructure.
• Experience mentoring software engineers in a team setting, including design and code review.
• Experience building with LLMs and agents rather than just coding with them—retrieval over technical documents, agentic workflows, evaluation harnesses, or tool integrations.
• A point of view on where AI-assisted development helps, where it doesn't, and how to verify agent output in an environment where records end up in front of regulators. Tell us about it.