Staff Software Engineer, Applied AI Solutions

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

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 Staff Engineer, Applied AI Solutions, you will provide end-to-end architectural, design, and technical leadership across multiple teams delivering enterprise-grade AI and Generative AI solutions. As a hands-on technical leader and architect, you will own system design decisions, define reference architectures, and guide implementation of AI-powered capabilities, including deep learning models, LLMs, RAG solutions and agentic workflows across internal and external customer-facing applications. You’ll also mentor engineers, influence platform strategy, and ensure AI-driven systems are secure, resilient and production-ready. A successful candidate in this role is expected to collaborate effectively with the broader teams, and consistently deliver well-architected, scalable, secure, production-grade AI and Generative AI features supporting a variety of use cases and scientific products, with measurable impact on scientific workflows, customer outcomes and innovation velocity.

Key Responsibilities

• Provide software and systems architecture leadership including reference architectures, design standards, patterns, and best practices for AI and Generative AI platforms and solutions.
• Own high-level and low-level system design, including component architecture, data flows, integration patterns, and deployment strategies.
• Design and evolve cloud-native, event-driven, and API-first architectures for AI-enabled products and platforms.
• Design, develop, and integrate Generative AI systems using LangChain and LangGraph for agentic workflows and orchestration.
• Architect and implement agentic AI and RAG workflows, including data ingestion, chunking, embeddings, vector search, retrieval, tool calling, memory, and prompt engineering.
• Build and deploy LLM-powered services using Azure OpenAI, Anthropic Claude, and OpenAI-compatible APIs.
• Leverage Ollama for local and on-prem LLM system experimentation and evaluation.
• Integrate AI/Generative AI capabilities across enterprise platforms, and scientific applications and workflows.
• Actively contribute to hands-on development using Python and modern backend frameworks such as FastAPI.
• Design and build well-structured, maintainable, and extensible APIs supporting AI and data-driven workloads.
• Define and implement performance, scalability, security, reliability, and observability patterns for AI-driven services.
• Define and implement automated testing and evaluation strategies for Generative AI systems, including prompt testing, regression testing, and model evaluation pipelines.
• Partner closely with product managers, architects, and other engineers to translate requirements into reliable solutions, and deliver against agile/scrum commitments.
• Mentor and guide engineers on software architecture, system design and advanced Generative AI patterns.
• Actively participate in Communities of Practice, influencing engineering standards and AI/Generative AI adoption strategies across the organization.
• Communicate effectively with technical and non-technical stakeholders through clear documentation, architecture diagrams and design reviews.

Candidate Requirement:

Education and Experience:

• Bachelor’s degree in computer science, engineering, or a related technical field. Master’s degree preferred.
• 10+ years of industry experience in software engineering and developing AI solutions, including multiple years specializing in integrating production-grade AI/ML solutions.
• 5+ years of experience working in agile/scrum environments.
• 5+ years of hands-on experience building scalable backend systems with Python and REST APIs (FastAPI preferred).
• Proficiency with Git-based development workflows, CI/CD pipelines, and automated testing strategies.
• Proficiency with containerization and orchestration (Docker, Kubernetes).
• Practical experience integrating and operating LLMs using Azure OpenAI or Anthropic Claude, or OpenAI-compatible AP…