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.

Responsibilities

• 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
• Define operational controls for reliability, performance and incident response once in production
• Support secure access patterns and role-based controls aligned with the client's platform and governance requirements
• Contribute to technical documentation, handover materials, and knowledge transfer for ongoing operations

• Strong hands-on experience developing and deploying microservice-style, containerised applications in production
• Direct experience deploying applications to Azure Container Apps and/or Databricks Apps (or comparable serverless/managed container platforms)
• Experience integrating application deployments into an existing enterprise CI/CD pipeline - this is not a build-from-scratch CI/CD role
• Solid understanding of containerisation (Docker), environment promotion, and release management
• Experience with monitoring, logging and alerting tooling for production services
• Working knowledge of secrets management, RBAC and secure access patterns in Azure and/or Databricks
• Comfortable working directly with client IT/platform teams to align on deployment standards and constraints
• Familiarity with Git-based workflows and collaborative engineering practices
• Experience supporting production-grade AI or data platforms in enterprise environments
• Strong troubleshooting, communication, and stakeholder management skills

• Familiarity with Databricks Apps specifically, as distinct from general Databricks workloads
• Exposure to Azure DevOps as the consuming CI/CD platform
• Experience in FMCG/CPG or other regulated enterprise environments
• Exposure to QA automation and non-functional testing in cloud-native systems