Dev Ops Manager - Azure

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people.

We help organisations solve complex business challenges by combining deep domain understanding with modern data and AI capabilities.

Our teams work across strategy, analytics, engineering, and product delivery to create scalable, high-value solutions that improve decision-making, efficiency, and growth

We are looking for an experienced Senior DevOps Engineer to support production readiness and deployment of an Agentic Executive Scorecard. The client already operates a proven CI/CD process, so this is a deliberately specialist role rather than a traditional end-to-end DevOps position: the primary focus is defining and implementing how the application itself is deployed — most likely to an Azure Container App or a Databricks App - and ensuring its microservice-style components are packaged, deployed, monitored and operated reliably within the client's existing platform, CI/CD and governance standards. The ideal candidate has strong hands-on experience developing and deploying containerised, microservice-type applications, and is comfortable integrating into an established enterprise CI/CD pipeline rather than building one from scratch.

• Define and implement the deployment architecture for the application, most likely an Azure Container App or a Databricks App, in collaboration with the client's IT team
• Package and deploy microservice-style application components (APIs, orchestration services, front-end) as containerised workloads
• Integrate deployments into the client's existing CI/CD pipelines and promotion process, rather than building CI/CD from scratch
• Configure environment separation, scaling, networking and secrets management appropriate to the chosen deployment target
• Implement production monitoring, logging and alerting to take the solution reliably through Dev/Test/Prod
• Work closely with Software Engineers and the Lead AI Engineer to ensure backend, orchestration and front-end components are deployment-ready
• Support non-functional testing, release readiness, and path-to-production activities alongside the QA Engineer