Software Engineer
Software Engineering
Bengaluru, Karnataka, India
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 assigned and agreed in the team planning process; communicate progress, risks, and deviations in a timely manner. Code quality and maintainability: Contribute to code quality and maintainability by following coding conventions, improving readability, adding tests, and participating in code reviews. Robustness across configurations: Help ensure changes remain robust across configurations and do not disrupt critical laboratory workflows; collaborate with QA on verification and troubleshooting. Product support and prevention: Provide support for assigned product areas (including participation in 3rd line support as needed), investigate issues, propose fixes, and contribute to preventing repeat incidents. Stakeholder collaboration: Collaborate closely with stakeholders (Product Management, Requirements Engineering, QA, Documentation, Support/Services and adjacent engineering teams) to ensure solutions meet real-world needs. Continuous improvement: Propose improvements to internal procedures and team ways of working to increase efficiency and quality. Knowledge / Skills / Abilities Good verbal and written communication skills; able to communicate clearly with technical and non-technical stakeholders. Important asset: knowledge of Progress OpenEdge ABL (Progress 4GL), including reading/debugging existing code and applying coding conventions. Software engineering fundamentals: Solid software development fundamentals; able to implement moderately complex changes with guidance and learn the codebase effectively. AI literacy and responsible use: Strong AI literacy and responsible use of AI assisted tools (GitHub Copilot), including prompt hygiene, data handling (no sensitive customer/PHI in prompts), and licensing/IP awareness. GitHub Copilot experience: Hands-on experience with GitHub Copilot in VSCode (e.g., refactoring, unit test generation, and documentation support), combined with strong code review and execution-based validation practices. Problem solving: Problem-solving skills: able to break down problems, investigate issues, and propose practical solutions. Quality mindset: Writes clear, concise, well-tested code; applies coding conventions; monitors own work to ensure correctness and reliability. Engineering workflows and tooling: Comfortable working with Git-based workflows (branching, pull requests, and code reviews) and team tooling (e.g., Azure DevOps), including CI/CD where applicable. Data and SQL: Working knowledge of relational database concepts (preferably Progress OpenEdge) and SQL; able to reason about data models, performance, and data integrity. Business logic and UI design: Ability to design and build reliable business logic and user interfaces with usability/ergonomics in mind. Regulated SDLC experience: Comfort working in a regulated/quality-managed environment, including documentation, traceability, peer review, and adherence to applicable procedures and quality gates. Education and Experience Bachelor’s or master’s degree in Computer Science/Engineering (or equivalent through experience). Professional experience in software development (object-oriented environment), including design, implementation, testing, and maintenance of production systems. Experience with relational database management systems and enterprise application development. Experience in the health sector (e.g., LIS/LIMS/healthcare software) and/or working with integrations into external healthcare systems and instruments is an asset. Experience with Progress OpenEdge ABL (Progress 4GL), including debugging and maintaining enterprise codebases, is an asset. Any equivalent combination of education and/or experience providing the knowledge/skills/abilities listed above.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
- Department
- Software Development
- Locations
- India Bangalore
- Remote status
- Hybrid
- Employment type
- Full-time