Build, operate and optimise the cloud, DevOps, observability, security and deployment foundations required for enterprise AI solutions. Ensures AI applications can move safely from proof of concept to production with reliable environments, CI/CD, monitoring, cost control, access management and operational support.

Responsibilities

Design and maintain environments for AI applications, services, models and orchestration layers
Support Azure AI Foundry, Azure OpenAI, Azure App Service, Azure Functions, Container Apps and Kubernetes
Implement CI/CD pipelines for AI applications, backend services, frontends and infrastructure
Automate build, test, deployment and rollback processes
Implement logging, monitoring, alerting and dashboards for AI applications and platform components
Track latency, throughput, model/API usage, token consumption, error rates, uptime and cost metrics
Implement secrets management, identity and access controls, RBAC, network restrictions and secure configuration
Partner with Cybersecurity to support vulnerability management, penetration testing and security reviews
Enable cost visibility, usage tracking, reliability and production support for AI platforms
Create reusable deployment templates and platform patterns for the AI engineering team

Experience and education

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, monitoring, logging, alerting and securing cloud environments. Exposure to AI platforms, data platforms or modern application engineering environments. Azure Administrator, DevOps Engineer Expert or Solutions Architect certification preferred. Fintech, banking or telecoms background preferred.