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

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.
• A track record of building software that other engineers can operate, extend, and maintain, supported by clear documentation and deliberate knowledge transfer.
• Occasionally requires working weekends.
• Occasionally requires schedule flexibility.
• Occasionally requires extended hours to support launch and critical project timelines.
• Kairos Power is committed to building a diverse workforce that reflects the communities that we do business in. Kairos Power is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. We actively welcome people of different experiences, abilities, and perspectives.
• Kairos Power participates in E-Verify.
• Candidates only, no recruiters or agencies please.

Desired Qualifications

• Master’s or Ph.D. in computational science, physics, engineering, or a related discipline, particularly with research experience implementing numerical methods is desirable.
• Experience with containerization using Docker, Apptainer, or comparable tools is desirable.
• Experience with Python packaging and environment management, including Conda, and with versioned artifact publication is desirable.
• Experience with build systems such as CMake, and with compiler and dependency management for compiled software is desirable.
• Experience with CI/CD systems such as GitHub Actions, including pipeline design and release automation is desirable.
• Experience with performance profiling and optimization driven by measurement rather than assumption is desirable.
• Experience with software quality assurance practices and controlled software delivery is desirable.
• Experience with high-performance computing environments, including Slurm, Open OnDemand, MPI, and GPU computing is desirable.
• Experience with software quality assurance in a regulated or safety-conscious engineering environment is desirable.
• Experience with documentation tooling such as Doxygen or Sphinx is desirable.
• Experience with relational databases, backend APIs, or cloud platforms such as AWS or Google Cloud is desirable.
• Familiarity with infrastructure as code and the operational side of software delivery is desirable.
• Knowledge, Skills & Abilities
• Proficiency with Git, Linux, Bash, and SSH.
• Strong command of software design fundamentals, including object-oriented programming, data structures, and algorithms.
• Ability to systematically diagnose complex software, build, dependency, environment, and runtime issues and identify root causes.
• Ability to design and maintain reproducible software build, test, packaging, and delivery processes.
• Ability to apply software quality assurance principles, including traceability, testing, documentation, and controlled delivery, appropriate to the software being developed.
• Ability to communicate effectively with nuclear engineers, computational scientists, and other non-software specialists, and to translate their requirements into working software.
• Ability to work with a highly collaborative team.
• Ability to solve problems quickly and efficiently.
• Prioritizes and ensures safety of oneself and others.
• Ability to proactively collect, manage and transfer knowledge.
• Ability to create efficiencies when working on problems, challenges, and issues, where each improvement is tied to a measurable engineering need such as safety, reliability, performance, usability, or maintainability.
• Ability to exercise architectural judgment and to favor the simplest design that satisfies the requirement.
• Ability to give direct technical feedback, to receive it, and to change course when a review identifies a better approach.
• Ability to explain technical tradeoffs to engineers and scientists who are not software specialists.
• Ability to take operational ownership of software through its full lifecycle, including testing, documentation, support, and retirement.
• Physical Conditions
• Remaining in a stationary position, often standing, or sitting for prolonged periods
• Moving about to accomplish tasks or moving from one worksite to another
• Communicating with others to exchange information
• Environmental Conditions
• Remote work
• General office environment
• High-concentration, demanding and fast-paced.
• Safety and PPE
• Reading and interpreting hazardous warning signs
• Manipulating, cleaning and disposal of hazardous materials
• Travel
• Some travel may be required for workshops and project assistance.

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