Overview
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.
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