Work Schedule
Standard (Mon-Fri)
Environmental Conditions
Office
Job Description
Our Group
At SEMI SPA (Sample Preparation and Analysis), we develop software that automates Scanning Electron Microscope (SEM) operation for the semiconductor industry. Our solutions are used by leading semiconductor manufacturers, including Samsung, TSMC, Micron, Intel and SK Hynix.
We help customers develop next-generation processors and memory chips by enabling inspection, analysis and process optimization at nanoscale precision.
AI is creating new opportunities to automate, optimize and support microscope workflows. We are looking for a highly experienced software engineer who can help turn that potential into reliable, production-ready solutions, primarily deployed on-premises.
As part of an international team of scientists, software developers and engineers, you will shape how AI is applied across our products and engineering workflows. You will work on complex technical challenges, define architectural approaches and help grow AI engineering capabilities across the organization.
Daily Challenges
Design architectures for AI-enabled software integrated into complex microscope automation systems.
- Turn AI concepts and prototypes into reliable, maintainable production systems.
- Build and integrate AI agents, MCP servers and tool interfaces that safely expose product and engineering capabilities.
- Identify opportunities where AI can improve microscope operation, diagnostics, automation, user experience and engineering efficiency.
- Evaluate the feasibility, risks and trade-offs of AI/ML approaches, including when deterministic software is the better solution.
- Collaborate with scientists, software engineers, system engineers and product owners to translate domain needs into technical solutions.
- Contribute to architectural guidelines, technical roadmaps and reusable AI software components.
- Mentor engineers in applied AI, machine learning, agentic workflows, MCP-based integrations and production-grade software design.
Knowledge, Skills, Abilities
This is a senior role, but you do not need to meet every requirement. We are looking for someone with strong software engineering fundamentals, practical AI experience and the ability to solve complex, sometimes ambiguous problems.
You should have:
- Significant professional experience in software engineering, ideally working on complex products, platforms or distributed systems.
- Proven ability to design and evolve software architectures for complex technical challenges.
- Experience developing integration software for high-performance systems and components.
- Understanding of interoperability across programming languages, frameworks and technology stacks.
- Strong programming skills in C# and Python.
- Practical experience building AI-enabled software for production environments.
- Strong understanding of modern AI engineering concepts, including LLM applications, embeddings, RAG, agents, tool use, MCP servers, model integration and evaluation.
- Strong understanding of machine learning concepts and trade-offs, including model training, fine-tuning, inference, evaluation and monitoring.
- Understanding of on-premises AI/ML architectures, including deployment, performance, security, observability and operational constraints.
- Experience working in agile development environments with iterative delivery and cross-functional collaboration.
- Experience with modern software engineering practices, including code reviews, testing, CI/CD, documentation and maintainability.
- Experience with Docker, Kubernetes or similar deployment technologies.
- Ability to influence technical direction, review designs and share knowledge across engineering teams.
- Professional working proficiency in English.
- Eligibility for a passport and willingness to travel occasionally.
Nice to have:
- University degree in Computer Science, Software Engineering, Artificial Intelligence, Machine Learning or a related technical discipline.
Technologies We Use
C#, Python
- Docker, Kubernetes
- Linux, Windows
- LLMs, embeddings, RAG, AI agents, MCP servers
- ML model training, inference, evaluation and monitoring tools
- Git, GitHub, CI/CD
- SQL, PostgreSQL
- Jira, Confluence
