Solutions Architect (AI and Cloud)

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 environments
  • Design scalable, serverless and containerised ML solutions
  • Define Infrastructure-as-Code patterns (Terraform preferred)
  • Build and optimise CI/CD pipelines with automation at the core
  • Establish API standards, observability, and architectural best practices
  • Translate business challenges into robust technical solutions
  • Lead and mentor cross-functional teams
  • Continuously evaluate and adopt new technologies

What They’re Looking For

  • Strong experience designing and delivering cloud-native solutions
  • Deep expertise in AWS, Azure or GCP
  • Strong programming skills (Python and/or TypeScript)
  • Proven experience with Infrastructure-as-Code (Terraform/CloudFormation)
  • Experience building scalable AI/ML systems in production
  • Strong understanding of modern software and data architecture patterns
  • Ability 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.

Experience: 8 years required
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