Solutions Architect

 
Solutions Architect with a strong AI/Cloud specialism for a leading healthcare provider

Remote (UK-based client) | Contract| Senior Level (8+ years)
Outside IR35
Duration: Start May until end of 2026

We’re partnering with a fast-growing, innovation-led technology business building cutting-edge AI and cloud solutions for forward-thinking organisations.

They’re now looking for an AI Architect to design and deliver scalable, enterprise-grade AI/ML platforms, someone who can bridge deep technical expertise with real business impact.

The Opportunity

This isn’t a theory-heavy architecture role. You’ll be hands-on in shaping and delivering production-ready AI systems across complex cloud environments.

You’ll work closely with engineering, data, and business teams to turn ideas into scalable, secure, and high-performing solutions.

If you enjoy building, influencing, and solving real-world problems with AI, this is where you’ll thrive.

What You’ll Be Doing

Architect and deliver enterprise AI/ML platforms in cloud environmentsDesign scalable, serverless and containerised ML solutionsDefine Infrastructure-as-Code patterns (Terraform preferred)Build and optimise CI/CD pipelines with automation at the coreEstablish API standards, observability, and architectural best practicesTranslate business challenges into robust technical solutionsLead and mentor cross-functional teamsContinuously evaluate and adopt new technologies
What They’re Looking For

Strong experience designing and delivering cloud-native solutionsDeep expertise in AWS, Azure or GCPStrong programming skills (Python and/or TypeScript)Proven experience with Infrastructure-as-Code (Terraform/CloudFormation)Experience building scalable AI/ML systems in productionStrong understanding of modern software and data architecture patternsAbility to communicate complex ideas clearly to technical and non-technical stakeholders
Nice to have:
Healthcare experience, event-driven architecture, advanced Terraform, Azure expertise, data platforms, or exposure to the full data science lifecycle.