AI Engineering Practice Lead 80-100% (w/m/d)

h3AI Engineering Practice Lead 80-100% (w/m/d) /h3ulliFull-time /li /ulpbDatahouse /b combines the two core competencies of Data Science and Software to deliver a unique service offering, bringing together a team of experts in data analytics, statistics, programming, databases and project management. Datahouse is a wholly owned subsidiary of the Wüest Partner Group. /ppbThe role /b /ppAs AI Engineering Practice Lead, you connect architecture with delivery. Our AI Solution Architect shapes the technical direction of the WP-group's products, and our AI Engineers build the solutions. You lead the technical implementation of agentic systems, both in group-wide platform projects and in external client projects. You stay hands‑on and set the standard for the AI Engineering practice. /ppbWhat you'll do /b /pullibBuild group-wide platform projects: /b work with the AI Solution Architect to design and build the shared AI foundations behind the Wüest Partner Group's products. That includes agent frameworks, tool and data integrations, evaluation pipelines and governance. You make sure they can be reused across companies and use cases. /lilibLead agentic engineering in delivery: /b own the technical side of projects where AI agents plan, use tools and carry out multi-step workflows. You see them through from design to production. /lilibMake agents production-ready: /b set the standards for evaluation, guardrails, human-in-the-loop design, security (permissions, prompt injection, etc.), cost and latency control. /lilibSet engineering standards: /b define reference architectures, reusable components and best practices across the AI engineers, including the right use of retrieval and context engineering. /lilibLead engineers functionally: /b review designs and code, mentor engineers and raise the technical bar. /lilibWork with clients and the group: /b take part in scoping, effort estimates and technical pre-sales, and explain trade-offs (autonomy versus control, quality, cost, risk) in plain terms. /lilibKeep the practice current: /b assess new models, agent frameworks and protocols such as MCP, and decide what is ready for production. /liulli5+ years in software, data or ML engineering, including significant hands‑on experience building LLM-based systems in production /liliProven experience with agentic systems: tool and function calling, multi-step and multi-agent orchestration, state and memory management, and integration with APIs and enterprise systems /liliA clear method for evaluating and testing non-deterministic systems /liliSolid understanding of retrieval and context engineering as building blocks, not an end in themselves /liliStrong Python skills and very good software engineering practice (APIs, CI/CD, containers) /liliExperience setting technical direction for others, as a tech lead, staff engineer or similar /liliAwareness of data protection and regulatory requirements (Swiss nDSG, EU AI Act) /liliExcellent English language skills; German is a plus /li /ul /ulpbWhat we offer /b /pulliAttractive employment conditions /liliFlexible Work Smart concept with the option to work from home /liliA welcoming, professional and collaborative company culture with great events (company celebrations, croissant breaks, etc.) /liliStrong team spirit, flat hierarchies and a varied range of responsibilities /liliAn attractive workplace in the heart of Zurich with modern facilities /liliGenerous training and development budget, including dedicated time for learning, as well as other attractive fringe benefits /li /ulpDue to data protection laws, we can only accept applications via our career website. /ppFor recruitment agencies: Only direct applications will be considered. /ppWe look forward to hearing from you! /ppbDatahouse AG /b /ppBy clicking the link above or any third-party link within this posting, you are leaving this site and going to a third-party website where the third-party website's terms and privacy policy apply /p