Staff Engineer, Software

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer. DESCRIPTION: Join Thermo Fisher Scientific, the world leader in serving science, as a Staff Engineer, Software to make a meaningful impact. In this role, you will provide technical leadership and architectural guidance while developing innovative software solutions that enable our customers to make the world healthier, cleaner, and safer. Working in a supportive, multi-functional environment, you will design and implement sophisticated solutions across our product portfolio, from cloud platforms to scientific instrumentation. You will support the growth of other engineers, drive adoption of best practices, and help shape the technical direction of critical projects. This position offers the opportunity to work with advanced technologies while contributing to groundbreaking scientific discoveries. Key Responsibilities Architect, design, develop, and deliver scalable, secure, and maintainable software solutions for bioprocessing, industrial automation, instrumentation, and process applications. Develop reusable software components, backend services, REST APIs, integration layers, data pipelines, libraries, and reference architectures for use across multiple products and programs. Integrate software applications with equipment, instruments, PLC, SCADA, DCS, HMI, historians, MES, sensors, actuators, and enterprise/manufacturing systems using industrial communication technologies. Design solutions for acquisition, processing, storage, visualization, and analysis of equipment, sensor, process, operational, and time-series data. Drive software engineering best practices including object-oriented design, design patterns, code reviews, automated testing, source control, CI/CD, DevOps, deployment, and lifecycle management. Ensure software solutions address cybersecurity, data integrity, validation, software quality, reliability, and regulatory requirements for connected and regulated systems. Identify and implement practical AI/ML, Generative AI, and advanced analytics opportunities for process monitoring, anomaly detection, forecasting, predictive maintenance, troubleshooting, engineering productivity, knowledge retrieval, and decision support. Provide technical leadership through architecture guidance, design reviews, technology evaluation, mentoring, troubleshooting, and technical decision-making. Lead solutions from architecture and proof-of-concept through productization, testing, deployment, and lifecycle support while driving reuse, standardization, automation, and engineering productivity Required Qualifications 9–14 years of relevant experience in software engineering, industrial/process automation, electronics or electrical engineering, or related disciplines. Strong hands-on development experience in one or more languages such as C#, .NET, Java, or Python. Strong knowledge of software architecture, object-oriented design, design patterns, multithreading, networking, APIs, data structures, system integration, and scalable application design. Experience developing backend services, REST APIs, data pipelines, and applications using relational and/or NoSQL databases. Strong understanding of industrial/process automation, process control, instrumentation, sensors, actuators, control loops, process variables, and data acquisition. Working knowledge of PLC, SCADA, DCS, HMI, historians, MES and industrial protocols such as OPC UA, Modbus, EtherNet/IP, PROFINET, or MQTT. Experience with automated testing, source control, CI/CD, build automation, deployment, and modern DevOps practices. Strong architecture, troubleshooting, analytical, and problem-solving skills with the ability to translate business and product requirements into secure and scalable solutions. Demonstrated ability to lead technical initiatives, influence architectural decisions, mentor engineers, and work effectively with multidisciplinary teams. Working knowledge of AI/ML and Generative AI, including anomaly detection, predictive analytics, LLMs, RAG, intelligent assistants, AI governance, security, privacy, and responsible AI practices. Experience in bioprocessing, life sciences, pharmaceutical manufacturing, biotechnology, laboratory/instrumentation products, or process industries is highly desirable. Knowledge of GxP, validation, data integrity, PAT, APC, soft sensors, digital twins, or model-based approaches is an advantage.