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  • ID
    #55364613
  • Job type
    Full-time
  • Salary
    TBD
  • Source
    Sia
  • Date
    2026-10-12
  • Deadline
    2026-12-11

The roleWe are looking for a Microsoft/Azure Stack Engineer to join our Data Science & AI team as a consultant. This is a client-facing role first: most of your time is spent on client engagements, designing and building Azure infrastructure and platform solutions, advising on cloud strategy, and representing Sia's technical delivery capability directly to the client. Alongside that, you will get hands-on with AI on the side of the business: building demos and proofs of concept on Azure AI Foundry that support new client opportunities, rather than running or maintaining an internal platform. If you want client exposure plus a genuine way to build AI skills on top of your infrastructure expertise, this is a team where that combination is real.What you will doWork directly with client teams and stakeholders as a consultant, explaining technical trade-offs and architecture decisions in plain language.Design and implement Azure infrastructure, including networking, compute, storage, and identity components (Azure AD/Entra ID, VNets, App Services, AKS).Build and maintain CI/CD pipelines using Azure DevOps or GitHub Actions to support infrastructure-as-code deployments (Terraform, Bicep, or ARM templates).Manage and optimize Microsoft 365 and Azure governance, including security baselines, cost management, and compliance controls.Build demos and proofs of concept on Azure AI Foundry to support business development and potential client work.Troubleshoot and resolve infrastructure issues across hybrid and cloud-native environments.Advise clients on cloud migration strategy, landing zone design, and the Azure Well-Architected Framework.Collaborate with client IT teams, architects, and Sia consultants to deliver technical roadmaps and implementation plans.Document architecture decisions, runbooks, and operational procedures.Depending on seniority, mentor junior engineers and contribute to internal capability building within the Azure and AI practice.

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