AI adoption is moving quickly, but turning AI potential into useful, scalable solutions requires more than experimentation.
Our client is a mid-sized Healthcare business that is starting their AI journey with several key hires.
This role sits at the intersection of AI engineering, Microsoft’s low-code/no-code ecosystem and traditional pro-code development. You’ll be responsible for building practical AI solutions that can be adopted across the business, while helping shape the foundations, standards and approach for AI development at scale.
You’ll have the freedom to choose the right technology for the problem. That could mean building an AI assistant in Copilot Studio, automating a process through Power Platform, or developing a more sophisticated solution using Azure, Microsoft Foundry and pro-code technologies.
The goal is simple: build AI solutions that genuinely improve how the business operates.
The role
→ Design, build and deploy AI-powered solutions across different areas of the organisation, from initial concept through to production.
→ Develop AI assistants, agents and automation using Copilot Studio, Power Platform and Microsoft’s wider AI ecosystem.
→ Build more complex pro-code AI solutions where low-code/no-code platforms reach their limits, using technologies such as Python, APIs, Azure and Microsoft Foundry.
→ Assess each use case and select the right approach, combining no-code/low-code and traditional software engineering where appropriate.
→ Develop solutions using technologies such as RAG, AI agents, LLMs, APIs and intelligent automation.
→ Connect AI solutions to Microsoft 365, Azure, business applications and enterprise data sources.
→ Help establish and evolve the organisation's AI engineering standards, architecture and governance, ensuring solutions are secure, scalable and maintainable.
→ Work closely with business stakeholders to understand operational challenges, identify valuable AI use cases and translate them into working solutions.
→ Support the wider adoption of AI by demonstrating what is possible and helping teams move successful use cases from experimentation into production.
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What you'll need
→ Proven experience building and deploying AI solutions hands-on, rather than purely advising on AI strategy.
→ Strong experience with Microsoft's AI and automation ecosystem, ideally including Power Platform, Copilot Studio, Azure and Microsoft Foundry.
→ Experience across both no-code/low-code and pro-code development. You should be comfortable building quickly with platforms such as Power Platform, but equally able to write code when a more sophisticated solution is required.
→ Practical experience with technologies such as Python, APIs, LLMs, RAG, AI agents or similar AI engineering approaches.
→ A broad understanding of Azure, Microsoft 365, data integration, security and enterprise architecture.
→ The ability to take an AI use case from idea → prototype → production, rather than stopping at proof of concept.
→ Strong stakeholder management skills and the ability to explain technical AI concepts to non-technical audiences.
→ A pragmatic mindset: you know when to use no-code, low-code or pro-code and can combine them to deliver the best solution.
→ Fluent English and German (C1/C2).