Software Engineer II - AI & Generative AI Applications

Engineer II, Software Work Schedule Standard (Mon-Fri) Environmental Conditions Office

As part of the Thermo Fisher Scientific team, youll 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 worlds toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer. DESCRIPTION: We are seeking a highly motivated AI Engineer to design, develop, and deploy AI-powered solutions that enhance scientific and business applications. In this role, you will work with cross-functional teams to build and optimize Generative AI and Agentic AI applications, develop intelligent workflows, integrate Large Language Models (LLMs), and ensure scalable, reliable, and secure AI solutions. You will contribute to the full AI application lifecycle, from prompt engineering and model evaluation to deployment and continuous improvement.

: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field. 2+ years of experience in AI application development or software engineering. Strong proficiency in Python. Hands-on experience with LangChain , LangGraph , and agent-based application development. Experience developing autonomous and multi-agent AI workflows. Experience working with Ollama for local LLM deployment and inference. Experience integrating and working with Large Language Models (OpenAI, Anthropic Claude, Gemini, Llama, Mistral, or equivalent). Experience building Retrieval-Augmented Generation (RAG) applications. Experience designing AI agents using tools, tool calling, and function calling capabilities. Experience integrating external tools, APIs, databases, and enterprise systems into AI workflows. Strong knowledge of prompt engineering, prompt optimization, and prompt management. Experience implementing AI guardrails, output validation, content filtering, and responsible AI practices. Familiarity with vector databases such as ChromaDB, FAISS, Pinecone, or Azure AI Search. Experience consuming REST APIs and developing microservices. Experience with Git, Agile methodologies, and CI/CD practices. Strong debugging, analytical, and problem-solving skills. Excellent written and verbal communication skills.