Software Engineer in Test

About Us At Dimer Instruments we’re creating the next generation of laboratory and process analytical tools for the pharmaceutical market. Our products use multiple light-based spectroscopic methods to interrogate solutions containing molecules and particles, providing researchers not just with data but with organized information allowing them to make informed decisions, and providing automated Process systems with the feedback required for Quality by Design. At Dimer you’ll be working with a high-quality, high-performing, highly collaborative, and enjoyable team of Engineers and Scientists to create products that make a difference in the world. We have fun while we’re creating great products. Summary The Software Engineer in Test will own the automated safety net that lets Dimer Instruments ship high-quality releases fast. Reporting to the Head of Software, this engineer builds and maintains the test coverage, continuous-integration gates, and release process that keep our platform (a C++/CLI solver layer under a .NET 9 MAUI Blazor application) correct, reproducible, and trustworthy as the codebase evolves rapidly. The central challenge is scientific correctness: proving that a given input yields the right numeric result (Rh, A2/B22, Tm, Tagg) within tolerance, not merely that the application builds and the buttons work. This is a high-leverage role in a small, senior, AI-augmented team that releases roughly every two weeks. Our developers and AI coding agents produce a high volume of new functionality; this engineer’s job is to make that velocity safe. They will be a force multiplier who builds guardrails, not a gatekeeper who manually tests every build. The successful candidate will partner closely with application scientists, the quality lead, and other software developers to turn deep domain knowledge into executable, versioned tests, and to raise the discipline of how changes are specified, reviewed, and merged. Essential Duties and Responsibilities Build and own the automated test safety net across the application and instrument-data pipeline: golden-master / characterization tests that feed known input datasets and assert on scientific outputs (Rh, A2/B22, Tm, Tagg) within defined tolerances, plus expanded unit (xUnit/NUnit) and Playwright UI coverage.Own CI/CD in GitHub Actions: make the build-and-test and UI-test workflows fast, reliable, and enforced as required checks; eliminate flaky tests; and ensure the full application, not just the business layer, is built and exercised in CI.Partner with the other developers to bring the C++ wrappers into automated testing and convert silent calculation failures into loud, test-caught errors.Establish and steward merge discipline: right-sized pull requests that map to coherent, revertible change sets; substantive review beyond automated approval; and a firm “no merging on red” standard.Define “done”: create and maintain an acceptance-criteria and definition-of-done template, and lightweight tooling that drafts acceptance criteria and test stubs from tickets, leveraging our AI workflow.Stand up a release-candidate gate for each release cycle: an automated golden-dataset regression suite plus a fixed manual sign-off protocol run with the application scientist before ship.Improve regression triage and traceability: reproducible bug capture, a characterization test added for each fixed defect, and healthy branch and pull-request hygiene.Partner with application scientists and the quality lead to translate domain- and result-specific knowledge into executable, versioned tests.Develop and maintain comprehensive documentation for test strategy, CI/CD, and the release process.Participate in code reviews and provide constructive feedback to ensure code quality and adherence to best practices.Present work in an organized way for project/progress reviews and design reviews.Perform other tasks as assigned.Qualifications Bachelor’s degree in Computer Science, Software Engineering, or a related field.4+ years of experience in software development with a meaningful focus on test automation, quality/release engineering, or software-engineer-in-test (SDET) work.Strong C#/.NET (.NET 8/9), able to read and write application code, not only test scripts.Depth in test automation: unit testing (xUnit/NUnit), end-to-end/UI testing (Playwright or similar), and golden-dataset regression testing with tolerance-based assertions.Fluency with CI/CD, especially GitHub Actions (matrix/sharded builds, required status checks, artifacts, caching).Comfort designing failure-mode tests with deliberately bad, empty, or malformed inputs, and making silent failures loud.A pragmatic, reproducibility-first mindset and the ability to work autonomously in an AI-augmented workflow.Able to work independently and as part of a team.Must be able to understand and communicate well in English, both spoken and written, and be able to write documentation.Must be able to present work in an organized way for project/design reviews.Additional Skills Experience testing scientific, numerical, or data-heavy software, with an understanding of tolerance and reproducibility for computed results.Domain background in biophysics, protein characterization, or light scattering (or willingness to learn it fast).MAUI / Blazor / MudBlazor, Plotly.js, EF Core + PostgreSQL.Testing across native-interop boundaries (C++/CLI or P/Invoke).Exposure to regulated software (21 CFR Part 11, validation, audit trails).Familiarity with AI coding agents as part of the daily workflow.Experience in the pharmaceutical or scientific instrumentation industry is a plus.Physical Requirements When working in machine shop, chemistry, or optics lab, appropriate protective gear must be worn including eyewear, eye protection from laser or UV light, lab coats, and closed toed shoes. Work Environment Office space, optics lab, chemistry lab, warehouse, and electronics and optical manufacturing space. The employee may occasionally be exposed to moderate noise levels, e.g. from loud fans in electronics equipment. Travel may occasionally be required, e.g. to test labs, customer sites, for conferences and trade shows, or for training.