Senior Engineer, Scientific Software and Developer Platform, Modeling and Simulation

Job description

**Company Overview** Kairos Power is a new nuclear energy technology and engineering company whose mission is to enable the world’s transition to clean energy, with the ultimate goal to dramatically improve people’s quality of life while protecting the environment. This goal will be accomplished through the commercialization of the fluoride-salt-cooled, high-temperature reactor (FHR) that can be deployed with robust safety, affordable costs, and flexible operation to accommodate the expansion of variable renewables. **Job Summary** Kairos Power is looking for a Senior Scientific Software and Developer Platform Engineer to work within a small software and infrastructure team that supports the needs of our design, research, and development organizations. This is a hands-on individual contributor role. You will architect and build the scientific software, developer tooling, and delivery systems that nuclear engineers and computational scientists use to design and analyze nuclear power systems. The work spans Python and C++ development, computational modeling, build and packaging systems, reproducible artifact delivery, CI/CD, containerization, software quality assurance, and high-performance computing workflows. You will set software architecture direction, establish the design and maintainability standards the group works to, and raise engineering practice through design review, code review, and mentoring. The group favors simple, proportionate designs assembled from standard, well-supported technologies, and this role is expected to be a leading voice for that standard. Success means writing and shaping software that engineers other than its original author can operate, extend, and maintain. **Responsibilities** **Scientific and engineering software** - Design, implement, test, and maintain scientific and engineering software in Python and C++, including the implementation of computational modeling methods and numerical algorithms. - Own software architecture for internally developed engineering tools, selecting data structures, interfaces, and algorithms that match the actual problem rather than an anticipated one. - Profile and optimize performance where a measurable requirement justifies the work, and document the resulting characteristics. - Collaborate with nuclear and other non-software engineers to define software projects based on their needs for tools that support the primary mission of the company. **Build, packaging, and artifact delivery** - Own CI/CD for internally developed software using GitHub Actions or comparable systems, including automated testing, quality gates, and controlled release. - Build reproducible build and packaging pipelines for Python packages, Conda environments, and C++ binaries and libraries, including compiler and dependency management. - Own artifact publication and versioning, so that consumers can determine exactly what they are running and reproduce it later. - Diagnose and resolve compilation, dependency, environment, and runtime problems across the scientific software stack. - Establish and maintain container build and runtime patterns for Docker and Apptainer across development and high-performance computing use, and own base image currency and upgrade paths so that containers stay patched without breaking the workflows built on them. **Software quality assurance and controlled delivery** - Uphold internal software quality assurance requirements, and build the automation that makes compliance a property of the pipeline rather than a manual step. - Define the artifacts, records, and gates required for controlled software delivery, and make them reproducible from the build system. - Support software quality audits with evidence generated by tooling rather than assembled by hand. **Scientific computing platform** - Develop and support high-performance computing user workflows, including Slurm scheduling, Open OnDemand interactive access, MPI, and GPU computing. - Improve the day-to-day experience of the engineers and scientists who use these platforms, and reduce the friction in their modeling and simulation workflows. - Build self-service engineering workflows and documented paths that let users solve common problems without opening a request. **Engineering standards and mentorship** - Establish design, documentation, and maintainability standards that other teams use to develop and deploy code, and apply them consistently through technical design review and code review. - Review software produced across the group, including internal applications, so that no system depends on a single author. - Mentor engineers, transfer knowledge deliberately, and remove single-person dependencies through documentation and shared ownership. - Evaluate build-versus-buy decisions, and select standard, well-supported libraries and tools over custom frameworks unless a requirement clearly demands otherwise. - Choose the smallest design that meets the actual requirement, and identify and retire technical debt, premature abstraction, and unnecessary complexity. - Participate in the team’s engineering help queue for issues that require deep software expertise, and communicate resolutions clearly to the engineers who reported them. **Qualifications** - Bachelor’s degree in computer science, engineering, physics, mathematics, computational science, or a related technical field, or equivalent combination of education and practical experience. - 5+ years of relevant software engineering experience, including experience developing scientific, engineering, computational, or other technically complex software. - Strong and demonstrable experience developing scientific or engineering software, with depth in both Python and C++. - Experience implementing computational modeling methods, numerical methods, or comparable quantitative algorithms. - Demonstrated software architecture experience, including the ability to decompose a problem, define interfaces, and reason about maintainability, performance, and long-term cost. - Experience with automated testing, including unit and integration testing with frameworks such as PyTest or GoogleTest. - Proficiency with Git, Linux, Bash, and SSH. - Experience mentoring engineers and conducting design and code review, together with a demonstrated ability to accept and apply design feedback.