Software Engineer

Clinisys’ AI Philosophy: Building an AI-first organisation is central to Clinisys’ purpose and the impact we deliver. As a global provider of intelligent diagnostic informatics solutions, we build AI-enabled, cloud-based platforms to enhance diagnostic workflows across healthcare, life sciences, and public health. By applying intelligent technology thoughtfully and responsibly, we help laboratories and testing environments operate more effectively, generate meaningful insights at scale, and ultimately support healthier and safer communities. Operating across more than 30 countries, Clinisys expects all colleagues—regardless of role or function—to work confidently with AI-enabled tools, apply digital and analytical thinking, and continuously adapt as technologies evolve, must drive an AI first sense of purpose and urgency. GLIMS Application Context GLIMS (General Laboratory Information Management System) is a healthcare laboratory information system used to support and manage end-to-end laboratory workflows. The application covers a broad functional scope including patient identity and encounter management, order and result management, laboratory analytical workflows, result validation, reporting, and integration with external healthcare systems and instruments. GLIMS is a highly configurable system used across different customers, countries, and laboratory environments, meaning functional behavior varies by configuration, workflows, integrations, and regulations. Operating within a complex healthcare ecosystem, GLIMS quality depends on strong functional understanding, correct handling of healthcare data, robustness across configurations, and ensuring changes do not disrupt critical laboratory processes. Job Summary The Software Engineer (SE) for the GLIMS application contributes to the analysis, design, implementation, testing, and maintenance of GLIMS features and fixes. The SE translates requirements and functional specifications into workable programming code and delivers reliable, secure, maintainable changes in a regulated healthcare environment. The SE collaborates closely with Product Management, Requirements Engineering, QA, Documentation, and Support to ensure changes meet intended workflows and remain robust across highly configurable customer environments. The SE practices an AI-assisted, AI steered way of working and uses AI as a default accelerator across day-to-day SDLC activities (analysis, design, implementation, testing, documentation, troubleshooting) under team guardrails, with accountability for correctness, quality, security, privacy, and compliance. Tasks & Responsibilities  Software development (delivery with guidance): Develop GLIMS features/fixes across the software development lifecycle (analysis, design, implementation, unit testing, and maintenance), seeking input from more experienced engineers when needed.  AI-steered development: Work in an AI-steered engineering workflow (GitHub Copilot) where AI is used as the primary accelerator for drafting code, refactoring, and generating unit tests. The engineer remains fully accountable to critically review, validate, and verify all AI-generated output (correctness, security, privacy, performance, and regulatory/quality requirements) before it is merged or released.  SDLC and quality-system adherence: Execute work in a defined, quality-managed SDLC by producing/maintaining appropriate design and technical documentation, ensuring requirements traceability, following change control, and meeting verification/validation evidence expectations (code reviews, unit/integration tests, QA validation) before release.  AI-assisted engineering artifacts: Use AI to draft and improve engineering artifacts (e.g., technical designs, test cases, edge-case checklists, troubleshooting hypotheses, and release notes), ensuring appropriate review and validation before content is relied upon or becomes part of the controlled record.  AI-driven incident investigation and operational fixes: Leverage a strong AI background and sound engineering practices to investigate complex customer incidents, perform efficient root-cause analysis, and implement reliable fixes for day to-day issues.  Requirements to implementation: Translate functional requirements/specifications into clear technical solutions and well-structured, tested code; raise questions early when requirements or designs are unclear.  Execution and communication: Execute daily development tasks as assig…