Staff Software Engineer, Applied AI Solutions
Thermo Fisher ScientificMatch Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessLog in to see why each signal reads the way it does.
Job Description
Structured overview of role & requirementsAbout This Role
Lead architectural design and technical leadership for enterprise-grade AI and Generative AI platforms across multiple teams.
Own system design decisions, reference architectures, and implementation of AI-powered capabilities including LLMs, RAG, and agentic workflows for internal and external applications.
Mentor engineers, influence platform strategy, and ensure AI-driven systems are secure, scalable, resilient, and production-ready with measurable impact on scientific workflows and customer outcomes.
Minimum Requirements
Bachelor’s degree in computer science, engineering, or related technical field (Master’s preferred).
10+ years industry experience in software engineering with AI solutions; includes production-grade AI/ML integration experience.
5+ years hands-on experience building scalable backend systems with Python and REST APIs (FastAPI preferred).
Proficiency with Git workflows, CI/CD, containerization (Docker, Kubernetes), and experience integrating LLMs via Azure OpenAI, Anthropic Claude, or OpenAI-compatible APIs.
Ideal Candidate Profile
Experienced in end-to-end AI system architecture and hands-on design of GenAI, RAG, and agentic AI workflows using tools like LangChain, LangGraph, and vector search technologies.
Demonstrated ability to lead cross-team architectural initiatives and mentor engineers within agile environments.
Strong backend development and data engineering skills coupled with experience in cloud-native, event-driven, and API-first architectures for complex AI-driven scientific applications.