AI Software Engineer
Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Sep 8, 2026. Thermo Fisher Scientific scores B on the Alion truth index.
Work Schedule
Standard (Mon-Fri)Environmental Conditions
OfficeJob Description
AI Software Engineer
Job Description
As part of the Thermo Fisher Scientific team, you'll 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.
As AI Software Engineer, you will develop AI-enabled scientific software that combines artificial intelligence, laboratory data, data engineering, and AI platform capabilities to accelerate laboratory automation and intelligent decision-making. You will also contribute to defining and evolving the organization’s AI architecture, AI operations framework, and technology standards, translating emerging AI technologies into practical and scalable engineering approaches.
[Key Competencies]
Solution-oriented with strong analytical and problem-solving skills.
Excellent communication and collaboration across internal, global, and customer-facing cross-functional teams.
Self-driven with the ability to rapidly evaluate new AI technologies and deliver production-ready software.
[Key Responsibilities]
Design, develop, test, and maintain AI-enabled scientific applications using modern AI and machine learning technologies.
Develop AI agents and intelligent workflows that integrate third-party AI solutions with digital laboratory applications.
Design and implement AI-driven analysis, reporting, and decision-support capabilities for laboratory workflows.
Build reusable AI services and APIs that enable scalable scientific AI capabilities across internal platforms and customer solutions.
Design and implement data pipelines and data integration services that enable AI-ready laboratory data.
Integrate and standardize data from ELN, LIMS, and other scientific software platforms for AI applications.
Support AI runtime environments, cloud-based AI services, and MLOps practices for reliable deployment of AI solutions.
Translate scientific and business requirements into scalable AI architectures and software solutions for both internal platforms and customer applications.
Collaborate with internal and global Product, AI, and Engineering teams to contribute to AI architecture, technology standards, integration patterns, and reusable capabilities across digital platforms.
Support customer demonstrations, Proof-of-Concept (PoC) activities, deployment, and continuous improvement of reusable AI and data engineering capabilities.
Develop and continuously improve AI operations practices, including model and prompt lifecycle management, observability, security, deployment, and operational monitoring.
Evaluate emerging AI technologies, frameworks, and third-party solutions through technical assessment and rapid prototyping, and recommend practical adoption approaches for the organization.
[Qualifications]
Education
Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related discipline.
Experience
3+ years of software development experience.
Recent Master's or Ph.D. graduates with strong software engineering and AI development foundations may also be considered.
Experience developing AI-enabled software applications, backend services, or AI platform components is plus.
[Knowledge, Skills, Abilities]
Strong programming skills in Python and modern AI development frameworks.
Understanding of AI/LLM architecture, cloud-based AI services, APIs, agentic AI frameworks, and modern AI development practices.
Knowledge of machine learning, LLMs, prompt engineering, and AI application development.
Experience or understanding of data pipelines, data integration, and data preparation for AI applications.
Ability to evaluate AI technologies and contribute to the design of scalable AI solutions, integration patterns, and reusable technical components.
Strong analytical, problem-solving, debugging, and software development skills.
Excellent communication and collaboration skills with customers and cross-functional teams.
Business-level English and Korean communication skills.
[Preferred Qualifications]
Experience with biotechnology, life sciences, laboratory automation, research, or scientific software environments is highly desirable.
Experience with Azure OpenAI, Semantic Kernel, LangGraph, or similar AI frameworks.
Experience with ELN, LIMS, Momentum, or scientific laboratory software.
Knowledge of laboratory automation workflows and scientific data management.
Familiarity with MLOps/LLMOps, AI observability, deployment, and operational monitoring is a plus.