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About the role
- AI Delivery Manager leading AI-powered and data-driven solutions at Convatec. Overseeing team and project execution with budgets up to $1.2 million.
Responsibilities
- Define and drive Convatec’s AI strategy in alignment with enterprise transformation goals, ensuring AI initiatives deliver measurable business value.
- Lead the end-to-end design, development, and deployment of AI-powered and data-driven solutions using Microsoft Azure AI services, Microsoft Fabric, and modern DevOps/MLOps practices.
- Directly manage a team of Engineers, providing technical guidance, mentoring, and performance oversight.
- Lead and coordinate workstreams involving over ten external consultants, including UX Lead, Power BI Lead, Fabric Architect, Enterprise Architect, cross-functional programme leads, and Data Analysts.
- Own the execution and delivery of AI and data projects with budgets up to $1.2 million, including planning, resource allocation, and stakeholder communication.
- Establish and enforce best practices in AI engineering, data architecture, and MLOps to ensure scalability, reliability, and compliance across all AI systems.
- Work closely with Convatec delivery teams and business units to ensure AI solutions are integrated effectively and aligned with operational needs.
- Make independent decisions on technical architecture, tooling, and delivery approaches within approved programme scopes.
- Approve resource allocation and task prioritisation within the AI CoE team and associated external consultants.
- Recommend and implement process improvements and technical standards without requiring prior approval.
- Authorised to approve technical documentation, solution designs, and internal project deliverables.
Requirements
- 5+ years’ experience in AI, ML, or Data Engineering, including at least 2 years in a technical leadership capacity.
- Strong expertise in Azure AI and ML services (Azure Machine Learning, Cognitive Services, Azure OpenAI).
- Proficiency with Microsoft Fabric, Azure Data Factory, and Synapse for large-scale data integration.
- Solid understanding of data engineering principles — data lakes, Lakehouse (Delta/Parquet), ETL/ELT design, and governance.
- Strong skills in Python, SQL, and API development (REST, GraphQL).
- Experience implementing DevOps/MLOps pipelines for deployment, testing, and monitoring.
- Proven ability to lead and mentor teams, set technical standards, and ensure delivery quality.
Benefits
- Flexible working
- Professional development opportunities
Job title
Job type
Experience level
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Not specified
Degree requirement
Tech skills
Location requirements
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