Software Engineering - Lab Automation and Software

This role develops C#/.NET-based software for laboratory automation platforms that connect instruments, workflows, data, and AI-enabled capabilities. The Software Engineer will deliver reliable instrument communication, desktop and back-end services, scientific data processing, diagnostics, reporting, and intelligent workflow integration for customer-facing automation products.

• →Design and develop C#/.NET software for laboratory automation, instrument control, data acquisition, diagnostics, and workflow execution.
• →Build instrument communication and control logic for analytical instruments, automation controllers, robotic or sample preparation devices, and connected laboratory systems.
• →Develop C# back-end capabilities including REST APIs, data services, background processing, configuration services, and system integration interfaces.
• →Apply asynchronous and concurrent processing patterns for real-time instrument events, automated workflows, and long-running tasks.
• →Develop scientific data capabilities including spectrum or chromatogram access, data transformation, file parsing, reporting, and result preparation.
• →Create desktop application components using WPF, WinForms, or related technologies for monitoring, configuration, diagnostics, and operator workflows.
• →Integrate AI-enabled features through APIs, service interfaces, tool execution, workflow triggers, or data-processing pipelines.
• →Improve software reliability, observability, performance, error handling, logging, diagnostics, and maintainability for customer-facing automation products.
• →Collaborate with front-end, AI Agent, data science, product, test, application, and instrument teams from design through delivery.
• →Contribute to technical design, code reviews, unit testing, integration testing, troubleshooting, documentation, and release readiness in alignment with Agilent quality and PLC expectations.

Qualifications

• Bachelor’s degree or above in computer science, software engineering, automation, electronic engineering, instrumentation, analytical science, or a related technical discipline.
• Minimum 5 years of hands-on C# software development experience, including strong experience with .NET Framework and modern .NET versions such as .NET 6, .NET 8, or later.
• Strong knowledge of object-oriented design, design patterns, modular architecture, clean code, maintainability, and software engineering best practices.
• Strong experience with asynchronous programming, multi-threading, concurrency control, deadlock prevention, performance troubleshooting, and long-running task management.
• Experience building desktop applications with WPF or WinForms for data display, instrument monitoring, configuration, or operator-facing workflows.
• Experience developing REST APIs, background services, data services, client-server communication, WebSocket, HTTP-based integration, or related enterprise service capabilities.
• Experience with relational databases such as SQL Server, PostgreSQL, or SQLite, including database design, data access, query optimization, and ORM frameworks such as Entity Framework.
• Ability to troubleshoot complex software issues across device communication, data acquisition, service integration, performance, reliability, or customer workflows.
• Strong collaboration skills with cross-functional engineering, product, test, application, and instrument teams.
• Ability to read technical documentation and participate in technical discussions in English; stronger English communication skills are a plus.

• Experience in laboratory automation, analytical instrumentation, medical device software, industrial automation, or scientific workflow applications.
• Hands-on exposure to instrument protocols or device integration such as hardware APIs, SDKs, serial communication, TCP/IP, device drivers, command execution, or diagnostics.
• Familiarity with TypeScript, Node.js, or JavaScript-based service components for AI Agent workflows, API integration, tool calling, orchestration logic, or back-end workflow automation.
• Familiarity with Python for data processing, scientific computation, automation scripting, AI/ML service integration, prompt or tool workflow support, or rapid prototyping.
• Experience with scientific data workflows, including chromatography or mass spectrometry data processing, spectrum or chromatogram analysis, file parsing, data conversion, quantitative review, or scientific reporting.
• Exposure to AI-enabled software integration, including AI Agent services, model inference APIs, tool execution, workflow triggers, orchestration, or data-processing pipelines.
• Familiarity with Angular, Electron, or modern front-end technologies for hybrid desktop applications, workflow user interfaces, or instrument-facing user experiences.
• Experience with CI/CD, automated testing, logging, monitoring, deployment packaging, or quality-sensitive product delivery processes.