Staff Software Engineer – Lab Automation

Key Responsibilities

• Provide technical leadership and architectural direction for instrument-control software, graphical user interfaces, laboratory automation, workflow orchestration, and AI-enabled instrumentation.
• Design and develop automation frameworks that orchestrate instruments, robotics, devices, and software services into reliable end-to-end laboratory workflows, including sequencing, instrument state management, synchronization, exception handling, and fault recovery.
• Design and integrate AI-enabled capabilities for intelligent troubleshooting, workflow and protocol assistance, instrument knowledge retrieval, run-data interpretation, anomaly detection, and context-aware automation in instrument control and laboratory automation software.
• Develop AI-driven automation capabilities that combine instrument state, workflow context, scientific knowledge, and operational data to generate or adapt workflows, monitor execution, respond to exceptions, and recommend or initiate controlled actions within defined safety and control boundaries.
• Apply appropriate evaluation, testing, monitoring, security, data protection, traceability, and human oversight to AI-enabled solutions.
• Diagnose complex issues involving application software, instrument communication, hardware, firmware, scripts, and laboratory workflows.
• Translate scientific, customer, system, and business requirements into reliable technical solutions.
• Define reusable instrument and device abstractions, APIs, data models, and communication patterns that enable interoperability and orchestration across instrument platforms and provide governed interfaces for AI-enabled automation.
• Collaborate with cross-functional and geographically distributed teams.
• Help define and execute the long-term technical roadmap for connected instruments, intelligent instrument-control software, and interoperable laboratory automation, including opportunities for AI-driven and increasingly autonomous workflows.

Minimum Qualifications

• Advanced degree with at least 6 years of professional software development experience, or bachelor’s degree with at least 8 years of professional software development experience.
• Degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, Automation Engineering, or related technical field.
• Advanced proficiency in one or more programming languages, such as Python, Java, C++ with demonstrated experience designing and delivering production-quality software systems.
• Experience developing, integrating and supporting software for scientific instruments, laboratory automation, robotics, medical devices, industrial equipment, or other hardware-controlled systems.
• Experience developing instrument-control applications, graphical user interfaces, engineering utilities, simulators, or diagnostic tools using technologies such as .NET/WPF, WinUI, Qt, or comparable frameworks.
• Experience integrating instruments or automation systems using vendor SDKs, REST APIs, messaging, serial communication, TCP/IP, OPC UA, file-based interfaces, or comparable communication mechanisms.
• Strong understanding of software architecture, object-oriented or modular design, design patterns, data structures, APIs, and hardware abstraction.
• Experience with asynchronous programming, multithreading, event-driven design, instrument state management, and fault recovery.
• Experience integrating software with embedded controllers, sensors, robotics, firmware, or other hardware components.
• Strong scripting and automation skills using Python, PowerShell, Bash, or comparable technologies.
• Experience applying AI technologies or AI-assisted development tools to engineering, scientific instrumentation, or automation use cases.
• Experience working within Agile or Scrum development methodologies.

Preferred Qualifications

• Experience developing scripts, protocols, or workflows for laboratory automation or liquid-handling platforms.
• Experience developing instrument-control applications, touchscreen interfaces, engineering utilities, simulators, or diagnostic tools.
• Experience working with instrument telemetry, operational logs, run data, scientific data, or service diagnostics.
• Experience deploying AI capabilities in local, edge, offline, or resource-constrained instrument environments.
• Familiarity with regulated product development, including documentation, requirements traceability, cybersecurity, risk management, verification, validation, and design controls.