AI engineer in manufacturing

Oroox is a software company headquartered in Liechtenstein, with international development teams. Our Manufacturing Commerce Cloud helps manufacturers automate quoting, ordering and the workflows surrounding production. We connect engineering, commercial processes and customer self-service for custom-manufactured parts. We are now expanding the use of AI across our product and internal operations. As our Lead AI Engineer, you will take technical ownership of this transformation. You will define the architecture, build the first applications and guide our engineering teams as we expand.

• Design a secure, reusable AI architecture for internal applications and customer-facing product features.
• Select and evaluate language models, deployment options and development tools against quality, privacy, performance and cost requirements.
• Build applications using retrieval-augmented generation, structured outputs, tool calling and controlled agent workflows.
• Establish secure access to internal knowledge and systems, respecting user permissions and data boundaries.
• Introduce AI-assisted software development with clear standards for human review, code ownership and architectural control.
• Develop product capabilities such as an Engineering Advisor, explanations of quotation and manufacturability results, and assistance with process configuration.
• Connect AI applications to existing geometry, pricing and manufacturing services.
• Establish evaluation datasets, monitoring and release criteria.
• Mentor engineers and document architectural decisions.

• Strong professional experience in software engineering, including ownership of production systems and architectural decisions.
• Demonstrated experience building and deploying LLM applications used in real business workflows.
• Strong backend development skills in Python and/or another established backend language.
• Practical experience with APIs, databases, automated testing, CI/CD and cloud infrastructure.
• Experience with retrieval, embeddings, tool calling and evaluation of model outputs.
• A solid understanding of authentication, authorization, secrets management and secure data handling.
• The judgment to determine where AI adds value and where established algorithms and explicit business rules are required.
• Professional English and the ability to collaborate across international teams.
• Будет плюсом: Microsoft Azure and enterprise identity management; Self-hosted models and private model deployments; CAD, manufacturing, ERP, quoting or other engineering software; Multi-tenant SaaS applications; Introducing AI development tools across an engineering team

• Ownership of a strategically important initiative.
• Direct collaboration with company leadership and experienced software engineers.
• Practical engineering challenges involving geometry, manufacturing and business automation.
• The opportunity to shape both our product and how our teams work.
• Compensation based on experience, responsibility and location.