Forward Deployed AI Engineer

As a Forward Deployed AI Engineer , you’ll lead the delivery of AI-powered solutions from concept to production. Working closely with business stakeholders, you’ll design, build and deploy AI workflows using Azure AI, Copilot Studio, Microsoft Fabric and enterprise platforms such as SAP and Salesforce, helping drive AI adoption across ConvaTec.

What Success Looks Like

• AI-enabled workflows delivered on time, within scope and adopted by business teams without significant rework.
• Zero critical failures on deployed workflows at point of handover; safe fallback behaviour verified across all production pipelines.
• All workflows pass AI Landing Zone governance review first time with complete, well-documented technical evidence.
• Measurable reduction in manual effort, cycle time or operational cost within re-engineered business processes.
• Reusable workflow patterns and components adopted across multiple Convatec initiatives.
• AIOps pipelines in place for every production workflow; issues identified and resolved proactively rather than reactively.
• Business and operational teams independently maintaining and extending AI-enabled workflows post-handover.
• Applied AI Engineers and other initiative team members visibly guided and upskilled through working alongside this role.
• Positive satisfaction ratings from business stakeholders on embedded delivery quality, pace and technical credibility.

About Role

• Partner with business stakeholders to identify opportunities and deliver AI-powered solutions that solve real business challenges.
• Design, build and deploy AI workflows and automation solutions using Azure AI, Copilot Studio and Microsoft Fabric.
• Integrate AI solutions with enterprise platforms, including SAP, Salesforce and other business systems.
• Own the end-to-end delivery lifecycle, from requirements and solution design through to deployment and operational handover.
• Implement AIOps/LLMOps, MLOps and monitoring practices to ensure solutions are scalable, reliable and production-ready.
• Provide technical leadership and guidance to engineers, analysts and project teams.
• Develop prototypes and proof-of-concepts to validate ideas and accelerate delivery.
• Establish engineering standards, best practices and reusable patterns that support AI adoption across the organisation.
• Ensure solutions meet security, compliance and governance requirements.
• Drive continuous improvement by evaluating new technologies and identifying opportunities to maximise business value.

About You

• 4-5+ years’ experience in software engineering, AI/ML workflow delivery or systems integration, with a demonstrable track record of full-stack delivery in production AI environments.
• At least 2 years operating in a senior or lead technical capacity, making independent architectural decisions and guiding other engineers without formal line management authority.
• Hands-on, production-grade experience across MLOps and AIOps - CI/CD pipeline ownership, model versioning, automated testing and live system monitoring - not as adjacent knowledge but as daily practice.
• Strong proficiency in Python and SQL; solid REST and event-driven API integration experience including enterprise systems such as SAP (via SAP Joule) or Salesforce.
• Hands-on experience with Azure AI Foundry, Microsoft Copilot Studio and Microsoft Fabric in production delivery contexts.
• Demonstrated ability to self-direct across the full delivery lifecycle - from discovery and design through to production deployment and business handover - without close technical supervision.
• Experience working directly with business stakeholders: translating operational requirements into engineering decisions, managing expectations and owning adoption outcomes.

Desirable

• Experience with SAP Joule or integrating agentic AI solutions with SAP business processes.
• Familiarity with AI Landing Zone design patterns, guardrails and governance frameworks.
• Experience with containerisation (Docker/Kubernetes) and cloud-native deployment patterns on Azure.
• Understanding of multi-agent coordination patterns using Copilot Studio or Azure AI Foundry.
• Knowledge of healthcare data privacy requirements including GDPR or HIPAA.

Education/Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Systems or a related field, or equivalent practical experience demonstrated through a strong delivery track record.
• R…