You'll work at the intersection of Platform Engineering, AI Infrastructure, and Developer Experience, building self-service environments, model and API access, deployment workflows, and reusable infrastructure for AI teams.

What You'll Work On• Build an internal developer platform specifically for AI engineering teams• Create self-service workflows through Backstage• Provision development, testing, and production environments on Kubernetes• Build reusable infrastructure components using Terraform• Develop platform tooling and automation in Python• Integrate LLM and model APIs into standardised developer workflows• Build secure, reusable access patterns for models, APIs, data, and infrastructure• Implement GitOps-based deployment workflows• Create golden paths for common AI application architectures• Automate environment provisioning and lifecycle management• Improve developer experience across experimentation, testing, deployment, and production• Build platform abstractions that reduce infrastructure complexity for AI engineers• Partner with AI, ML, Platform, and Security teams to standardise how AI systems reach production

Core Skills• 4+ years in Platform Engineering, AI Infrastructure, MLOps, Developer Experience, or similar roles• Kubernetes• Python• Backstage• Terraform• LLM / model APIs• GitOps• AWS• Strong understanding of self-service developer platforms

• Nice to HaveArgo CD / Flux

You'll work at the intersection of Platform Engineering, AI Infrastructure, and Developer Experience, building self-service environments, model and API access, deployment workflows, and reusable infrastructure for AI teams.

What You'll Work On• Build an internal developer platform specifically for AI engineering teams• Create self-service workflows through Backstage• Provision development, testing, and production environments on Kubernetes• Build reusable infrastructure components using Terraform• Develop platform tooling and automation in Python• Integrate LLM and model APIs into standardised developer workflows• Build secure, reusable access patterns for models, APIs, data, and infrastructure• Implement GitOps-based deployment workflows• Create golden paths for common AI application architectures• Automate environment provisioning and lifecycle management• Improve developer experience across experimentation, testing, deployment, and production• Build platform abstractions that reduce infrastructure complexity for AI engineers• Partner with AI, ML, Platform, and Security teams to standardise how AI systems reach production

Core Skills• 4+ years in Platform Engineering, AI Infrastructure, MLOps, Developer Experience, or similar roles• Kubernetes• Python• Backstage• Terraform• LLM / model APIs• GitOps• AWS• Strong understanding of self-service developer platforms

• Nice to HaveArgo CD / Flux