AI Stack Development Lead

Own the solution design and technical roadmap for the AI stack on Microsoft Fabric, integrated with Azure AI Foundry and Azure OpenAI Evaluate and integrate data science and MLOps platforms such as Dataiku, Azure Machine Learning or Databricks Build data governance foundations for AI with tools such as Collibra or Informatica, covering cataloguing, lineage, quality and master data Define AI development guidelines and responsible AI standards across the full lifecycle of models and agents Lead model selection and rationalisation, weighing LLMs and SLMs on capability, latency and cost Set and enforce token consumption and cost governance, including budgets, dashboards, chargeback and optimisation Own standards and governance for Microsoft Copilot Studio agents alongside Fabric and Azure based agents Design integrations between AI solutions and SAP (S/4HANA, Datasphere), Cognite Data Fusion and other OT/IT platforms Champion everyday AI adoption through Microsoft 365 Copilot and low code agent builders, within agreed guardrails Present architecture decisions, costs and value delivered to executive forums Lead, mentor and grow a small team of engineers and developers

Desired Candidate Profile

Bachelor's degree in Computer Science, Data Science, Engineering or similar; a Master's is preferred 12+ years in data and AI, including 5 to 8 years hands on in AI, machine learning or advanced analytics Production AI/ML delivery in enterprise, industrial or manufacturing environments Deep, hands on Microsoft Fabric expertise (Data Factory, OneLake, Lakehouse, Synapse Data Science, Real Time Intelligence, Power BI) Experience with Dataiku, Databricks, Azure Machine Learning or similar, plus Collibra or Informatica Hands on Microsoft Copilot Studio experience Proven experience with LLM cost governance, token monitoring and model rationalisation (FinOps for AI) Experience integrating AI with SAP and industrial platforms such as Cognite Familiarity with frameworks such as NIST AI RMF, ISO/IEC 42001 or the EU AI Act Knowledge of Semantic Kernel, LangChain/LangGraph or MCP based tool integration is highly desirable Strong Python and SQL At least 4 to 5 years leading or mentoring technical teams YOU LL THRIVE HERE IF YOU Are equally comfortable setting enterprise standards and getting into the detail of a solution design Treat AI spend as seriously as AI capability Enjoy turning complex, messy industrial data into something the business actually uses Can explain architecture choices to a CEO as clearly as to an engineer Like working across several operating companies and countries