Additionalinformation

Additional Information

What we offer

• Attractive employment conditions
• Flexible Work Smart concept with the option to work from home
• A welcoming, professional and collaborative company culture with great events (company celebrations, croissant breaks, etc.)
• Strong team spirit, flat hierarchies and a varied range of responsibilities
• An attractive workplace in the heart of Zurich with modern facilities
• Generous training and development budget, including dedicated time for learning, as well as other attractive fringe benefits

Contact

If you have any questions, please feel free to contact Katharina Senning, Senior Talent Acquisition Specialist, at [email protected].

Due to data protection laws, we can only accept applications via our career website.

For recruitment agencies: Only direct applications will be considered.

We look forward to hearing from you!

Datahouse AG

Companydescription

Company Description

Datahouse 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.

Jobdescription

Job Description

The role

As 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.

What you'll do

• Build group-wide platform projects: 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.
• Lead agentic engineering in delivery: 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.
• Make agents production-ready: set the standards for evaluation, guardrails, human-in-the-loop design, security (permissions, prompt injection, etc.), cost and latency control.
• Set engineering standards: define reference architectures, reusable components and best practices across the AI engineers, including the right use of retrieval and context engineering.
• Lead engineers functionally: review designs and code, mentor engineers and raise the technical bar.
• Work with clients and the group: take part in scoping, effort estimates and technical pre-sales, and explain trade-offs (autonomy versus control, quality, cost, risk) in plain terms.
• Keep the practice current: assess new models, agent frameworks and protocols such as MCP, and decide what is ready for production.

Qualifications

• 5+ years in software, data or ML engineering, including significant hands-on experience building LLM-based systems in production
• Proven 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
• A clear method for evaluating and testing non-deterministic systems
• Solid understanding of retrieval and context engineering as building blocks, not an end in themselves
• Strong Python skills and very good software engineering practice (APIs, CI/CD, containers)
• Experience setting technical direction for others, as a tech lead, staff engineer or similar
• Awareness of data protection and regulatory requirements (Swiss nDSG, EU AI Act)
• Excellent English language skills; German is a plus