AI Platform & DevOps Engineer

Deliverables Establish clear delivery patterns and reusable assets for priority AI use cases. Support at least two to four high-priority MVPs/pilots moving from discovery into controlled pilot or production readiness. Create documentation, reusable code, deployment patterns, evaluation methods and operational practices that reduce future delivery effort.

Demonstrate measurable improvements in delivery speed, automation, user productivity, AI quality, operational efficiency or cost avoidance. Build credibility with business stakeholders by delivering practical, secure and usable AI solutions rather than conceptual prototypes.

Technical Skills and Capabilities Azure platform services, Azure AI Foundry, Azure OpenAI and cloud application hosting CI/CD using GitHub Actions, Azure DevOps or equivalent Docker, containers, Kubernetes, Azure Container Apps or equivalent Infrastructure-as-code using Terraform, Bicep or ARM templates Monitoring and observability using Azure Monitor, Application Insights, Log Analytics or equivalent Secrets management, Key Vault, managed identity, RBAC and secure networking API Management, gateways, service endpoints and integration infrastructure Cost management, usage dashboards and cloud optimization practices Linux, scripting, Python, Bash and automation tooling Operational support, incident management and production readiness practices Required Qualifications and Experience 5+ years in DevOps, cloud engineering, platform engineering, site reliability engineering or infrastructure engineering. 2+ years supporting cloud-native applications or enterprise platforms.

Experience implementing CI/CD pipelines and automated deployments. Experience with monitoring, logging, alerting and operational support. Experience securing cloud environments and managing identity, secrets and access controls. Exposure to AI platforms, data platforms, APIs or modern application engineering environments.

Preferred Qualifications and Experience Microsoft Azure Administrator, Azure DevOps Engineer Expert, Azure Solutions Architect or equivalent certifications. Experience supporting AI/ML platforms, LLM applications, model endpoints or data science environments. Experience in regulated environments such as fintech, banking, telecoms or enterprise technology.

Experience with Kubernetes, API gateways, vector databases and enterprise search services. Experience with cost governance for AI/API usage and cloud services. Please note only shortlisted candidates will be contacted. If you have not heard from us in 2 weeks, please consider your application unsuccessful.