Software Engineering Manager - Infrastructure

Software Engineering Manager - Infrastructure

Radiant is an El Segundo, CA-based startup building the world’s first mass-produced, portable nuclear microreactors. The company’s first reactor, Kaleidos, is a 1-megawatt failsafe microreactor that can be transported anywhere power is needed and run for up to five years without the need to refuel. Portable nuclear power with rapid deploy capability can replace similar-sized diesel generators and provide critical asset support for hospitals, data centers, remote sites, and military bases.

Radiant’s unique, practical approach to nuclear development utilizes modern software engineering to rapidly achieve safe, factory-built microreactors that leverage existing, well-qualified materials. Founded in 2020, Radiant is on track to test its first reactor next year at the Idaho National Laboratory, with initial customer deliveries beginning in 2028.

About the Role

Radiant is seeking a hands‑on Software Engineering Manager – Infrastructure to build and lead a team that scales our software infrastructure, developer tooling, and data processing capabilities. In this role, you will establish a platform function that serves as the backbone for Radiant’s engineering organization—enabling faster iteration on reactor designs, sophisticated Digital Twin simulation and visualization, and data‑driven analysis across the company.

You will work in a highly interdisciplinary environment to build products that accelerate our path to deploying the world’s first mass‑produced nuclear reactor.

Responsibilities

• Build, lead, and mentor a high‑performing team of platform engineers focused on internal tools, compute infrastructure, CI/CD pipelines, and data processing systems.

• Partner with engineering leaders across software, simulation, electrical, mechanical, and nuclear disciplines to identify infrastructure and tooling needs.

• Build infrastructure and tooling necessary to maintain high‑quality standards and detect issues in real time across engineering systems.

• Own the technical roadmap for internal developer tooling: CI/CD pipelines, version control systems, artifact management, build systems, developer environments, testing frameworks, and release processes.

• Architect and maintain full‑stack web applications that provide real‑time monitoring, Digital Twin visualizations, and analysis tools for Kaleidos reactor systems.

• Scale data processing infrastructure to support increasingly sophisticated simulation post‑processing, visualization, and analysis workflows.

• Foster a culture of engineering excellence through strong technical practices, automation, and continuous improvement.

• Recruit and develop top engineering talent while building a high‑performance team culture that enables organizational velocity.

Required Qualifications

• Bachelor’s degree in computer science, physics, mechanical engineering, or a related engineering field from an accredited institution.

• 7+ years of professional software engineering experience in data infrastructure, compute platforms, developer productivity, software tooling, or platform engineering.

• 2+ years of people management or technical leadership experience building and leading engineering teams.

• Strong software development expertise in programming languages such as Python, Golang, Rust, C#, or C/C++.

• Deep understanding of system design, data structures, algorithms, and distributed systems architecture.

• Extensive experience with build systems, data pipelines, and infrastructure automation.

• Proficiency with containerization (Docker), orchestration (Kubernetes), and infrastructure‑as‑code tools (Terraform, Ansible, etc.).

• Significant experience working in hybrid cloud/on‑premises environments, specifically AWS and Linux systems.

• Strong foundation in software engineering best practices (version control, code review, testing, CI/CD).

Preferred Qualifications

• Experience in highly regulated industries (aerospace, defense, automotive, nuclear, or medical devices).

• Background with simulation workflows, computational modeling, or scientific computing infrastructure.

• Hands‑on experience with big data processing technologies such as Spark,…