Software Engineer II, AI Solutions & Platforms

Work Schedule Standard (Mon-Fri)

Environmental Conditions Office

About the Role

At Thermo Fisher Scientific, you’ll do meaningful work that makes a positive global impact. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner, and safer. With industry-leading R&D investment, we empower our teams to solve complex scientific challenges—from environmental protection to advancing healthcare and cancer research.

As a Software Engineer, AI Solutions & Platforms, you will play a hands-on technical role in designing, developing, and delivering enterprise-grade AI and Generative AI solutions. You will build production-ready AI services, integrating AI models, including Large Language Models, Retrieval-Augmented Generation (RAG) solutions and agentic workflows into internal and external customer-facing systems. You will also contribute to system design and development using modern AI frameworks, backend technologies, and cloud platforms.

As a Senior Engineer, you will write production code, collaborate closely with architects and engineering teams, and contribute to technical and design decisions. You will help build AI-driven systems that are scalable, secure, reliable, and maintainable. A successful candidate in this role is expected to develop production-grade AI and Generative AI features, build reliable and high-performing backend services supporting AI workloads, contribute to high-quality code, collaborate effectively with the broader teams, and make a meaningful impact on our products and customer experiences.

Key Responsibilities

• Design, develop, and deploy production-grade Generative AI and backend applications using Python, FastAPI, LangChain, LangGraph and related technologies.

• Contribute hands-on to low- and mid-level system design, including APIs, service architecture, data models, workflows, and integrations with existing backend and scientific applications.

• Develop and maintain RAG and agentic AI workflows, including data ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, and prompt engineering.