AI Product Lead

𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗿𝗼𝗹𝗲

We're hiring a technical AI Product Lead to own the end-to-end lifecycle of our client’s AI products from problem framing and roadmap through to production deployment and adoption. You'll sit at the intersection of business, data science, engineering, and governance, translating strategy into shippable capability. This is the right role for someone who has taken AI/ML use cases from proof-of-concept to industrialized product inside complex, regulated environments, and who can hold both the technical detail and the executive narrative.

𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀

• Own the product vision, roadmap, and backlog for AI/ML use cases (e.g. document and process automation, monitoring/detection systems, client analytics), prioritizing against business value and feasibility
• Lead cross-functional delivery squads — data science, engineering, MLOps, and business analysis — as the connective tissue between technical build and business outcomes
• Drive PoC-to-production industrialization: define success criteria, manage the path to scale, and ensure solutions are robust, monitored, and maintainable
• Act as primary point of contact for business stakeholders and clients, gathering requirements, managing expectations, and communicating progress
• Partner with governance and risk functions to embed responsible-AI, privacy-by-design, and compliance requirements into the product from the outset
• Contribute to solution architecture decisions (LLM/agentic systems, data pipelines, feature and MLOps tooling) alongside technical leads
• Run Agile/Scrum ceremonies and own delivery planning, sprint execution, and release management
• Present product strategy, investment cases, and delivery updates to senior and executive stakeholders
• Support change management and AI-literacy efforts to drive adoption across business teams

𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲

• 7 + years in data/AI delivery, with meaningful time in a product ownership, product management, or delivery-lead capacity
• Track record shipping AI/ML products from concept to production in a regulated sector (financial services, healthcare, or public sector a plus)
• Experience leading cross-functional teams and managing complex, multi-stakeholder programs
• Comfortable owning a roadmap and making prioritization trade-offs against business value

𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗳𝗹𝘂𝗲𝗻𝗰𝘆

• Solid working understanding of the modern AI stack on Microsoft Azure: LLMs and agentic systems via Azure OpenAI / Azure AI Foundry, ML/NLP, and Azure Machine Learning — enough to challenge and collaborate with engineers, not necessarily to build alone
• Familiarity with the Azure data platform: Microsoft Fabric, Azure Data Lake Storage (ADLS Gen2), Delta Lake, and Azure Databricks, plus modern data architecture patterns (Data Mesh, Data-as-a-Service, ontology modeling)
• Understanding of MLOps/LLMOps practices in an Azure context — model deployment, monitoring, feature stores, and CI/CD (e.g. Azure DevOps / GitHub Actions)
• Exposure to Azure governance and security tooling relevant to regulated environments (Microsoft Purview, identity and access management, responsible-AI tooling)
• Comfortable with Python, SQL, Spark, and Docker, and with BI/analytics delivery through Power BI

𝗪𝗮𝘆𝘀 𝗼𝗳 𝘄𝗼𝗿𝗸𝗶𝗻𝗴

• Strong Agile/Scrum delivery discipline (Product Owner / Scrum Master experience valued)
• Grounding in AI and data governance and responsible-AI practices
• Excellent stakeholder management and executive communication

𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀

• University degree in computer science, engineering, or a related quantitative field (advanced degree a plus)
• Fluent English and French; German an advantage
• Eligibility to work in Switzerland

𝗬𝗼𝘂𝗿 𝗗𝗮𝘁𝗮

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