Sr. Manager, Gen AI Software Engineering

Senior Manager, Applied GenAI Engineering – Scientific AI Applications

Location:

This is a fully onsite position based at our Pleasanton, CA site. Unfortunately, relocation assistance is NOT provided.

Thermo Fisher Scientific is seeking a Senior Manager, Applied GenAI Engineering – Scientific AI Applications to lead the development of practical, high-impact Generative AI solutions for the Genetic Sciences business.

Division:
Genetic Sciences

Discover Impactful Work

• This is a hands-on technical leadership role with strong software engineering judgment, deep understanding of modern AI systems, and the ability to bring structure to new and emerging technology. The ideal candidate understands the foundations of AI and can translate emerging capabilities into reliable, scalable, and secure products for scientific and healthcare applications.
• You will lead a focused team of AI engineers, software engineers, data scientists, and algorithm developers to build GenAI-powered applications, assistants, agents, and productivity tools that improve how scientific knowledge is captured, searched, reasoned over, and applied.
• We are looking for a pragmatic, hands-on, intellectually curious technical leader who can move effectively between strategy, architecture, experimentation, and team leadership.

Key Responsibilities

• Lead the design, development, evaluation, and deployment of GenAI-powered applications, assistants, automation agents, and AI-enabled product development tools.
• Partner with product and business teams to define AI use cases, prioritize opportunities, and align solutions with customer needs and business goals.
• Define secure, scalable, and cost-effective AI architectures using LLMs, retrieval-augmented generation, agentic workflows, fine-tuning, structured evaluation, and human-in-the-loop feedback.
• Build and guide prototypes, proof-of-concepts, and production implementations using modern GenAI frameworks, APIs, cloud services, and software engineering practices.
• Develop domain-specific AI capabilities that leverage Thermo Fisher Scientific's Genetic Sciences knowledge, data, workflows, and product expertise.
• Partners with IT, data platform, cybersecurity, and cloud teams to enable infrastructure for model experimentation, fine-tuning, deployment, monitoring, and governance.
• Establish practical AI evaluation methods, including benchmarks, accuracy measurement, robustness testing, hallucination reduction, traceability, security, latency, and cost optimization.
• Stay current with advances in Generative AI, agentic systems, model architectures, evaluation techniques, and AI engineering practices, and apply them to scientific and healthcare challenges.

Keys to Success

• The successful candidate will be someone who can:
• Understand the mathematical and technical principles behind modern AI systems, not just use AI APIs.
• Build and guide GenAI applications from concept through production deployment.
• Turn high-potential, ambiguous ideas into executable technical roadmaps.
• Lead by example through hands-on technical contribution, sound engineering judgment, and strong collaboration.
• Inspire teams with enthusiasm, curiosity, and a practical "can-do" mindset.

Education and Experience

Required

• Master's degree or higher in Computer Science, Data Science, Bioinformatics, Statistics, Mathematics, Engineering, or a related technical field.
• 8+ years of experience in software engineering, AI/ML, data science, or applied algorithm development.
• 2+ years of experience leading teams, projects, or engineering initiatives.
• Strong hands-on experience building AI/ML or GenAI systems using Python and modern AI/ML libraries.
• Solid understanding of machine learning fundamentals, statistics, probability, optimization, deep learning, embeddings, transformers, and LLM behavior.
• Experience developing GenAI applications using platforms such as OpenAI, Anthropic, Gemini, Amazon Bedrock, Azure OpenAI, or similar.
• Experience with retrieval-augmented generation, prompt engineering, vector databases, evaluation frameworks, agentic workflows, or model fine-tuning.

Knowledge, Skills, and Abilities

• Demonstrated ability to mentor technical talent and build a high-performing…