AI Technology Lead (m/f/d)

Das ist der Job

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Darum lohnt es sich

CAD/CAE/PLM, automation, digital twins) Exposure to rule‑based systems, engineering constraints, or safety‑critical environments Benefits A defining role in building a new category of engineering software Direct influence on product architecture and strategy Highly competitive compensation, long‑term growth path A growing company with a motivated team and helpful colleagues Flexible working hours and a hybrid working model 30 days annual leave An individual onboarding program High‑quality advanced training A good working atmosphere with an open feedback culture Benefits package including: company pension plan (CPP), capital‑forming benefits, employee benefits, Ticket Plus Card (Edenred), JobBike Equal Opportunity Employer WSCAD is part of the Buhl group with approx. 800 employees.

AI Technology Lead (m/f/d) Working time model: Full-time Working model: Hybrid Main place of work: Bergkirchen near Dachau Start date: immediately Engineering software is at a structural turning point.

At WSCAD, we are building the next paradigm: AI-native engineering systems, where AI is not an add‑on, but the core operating layer of engineering workflows.

We are looking for an AI Technology Lead to architect this next-generation platform—a system that understands engineering intent, reasons across disciplines, and orchestrates workflows from concept to installation.

Responsibilities Architect the AI core of WSCAD’s engineering platform, embedding AI as the operating layer — not a service add‑on Design AI-native engineering workflows, including reasoning, rule interpretation, validation, constraint solving, and optimization Bridge AI, software architecture, and engineering domain knowledge, working closely with product, platform, and electrical engineering experts Set technical direction for AI at WSCAD, mentoring engineers and integrating state-of-the-art AI approaches where they deliver real engineering value Qualifications Strong software engineering background, with experience building production‑grade systems Solid experience in AI system design, including one or more of: applied machine learning AI systems engineering constraint solving or optimization symbolic and statistical AI approaches knowledge representation and reasoning Architectural mindset, comfortable designing platforms where AI is a core component Experience reasoning about data flows, model lifecycle, validation, explainability, and reliability in production Ability to work across disciplines and translate domain logic into robust system behavior Nice to have Experience with engineering or industrial software (e.g.

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