
Cloud Engineer – Design and Build Secure, Scalable Cloud Services
1 week ago
- Design and build secure, scalable cloud services on Microsoft Azure.
- Implement tenant isolation, rate limits, and API versioning using Azure App Service/AKS/Functions behind API Management.
- Integrate Azure ML with model registry/endpoints and Responsible AI Dashboard/Toolbox to generate fairness, error, and explainability reports.
- Implement Azure AI Content Safety checks in the prompt/response path.
- Connect datasets, prompts/outputs, and lineage to Microsoft Purview; build audit/reporting workflows (AI Foundry → Purview).
- Enforce Azure Policy baselines (networking, encryption, diagnostics), IAC for repeatable deployments.
- Build observability (App Insights/Log Analytics), SLOs, alerting, and secure secret management (Key Vault).
- Collaborate with Product and Compliance on governance features (access reviews, approvals, audit exports).
Required skills and qualifications include:
- 5+ years building cloud services (preferably Azure) with multi-tenant architectures.
- Hands-on experience with API Management, App Service or AKS, Functions, Key Vault, Azure Monitor/Log Analytics.
- Experience with Azure ML (endpoints/registry) and RAI tooling or equivalent ML governance stack.
- Proficiency in C#/.NET or Node.js/TypeScript or Python; SQL/Cosmos; CI/CD (GitHub Actions/Azure DevOps).
- Security/Compliance fundamentals: RBAC, Private Endpoints, encryption at rest/in transit; Azure Policy.
Nice to have are:
- Microsoft Purview (catalog, lineage, access policies) and Azure AI Foundry experience.
- Content moderation integrations (Azure AI Content Safety).
- Experience in regulated environments (health/finance), data residency/sovereignty.
This is a great opportunity for those who enjoy working with cloud technologies and want to make a difference in the field of AI governance.
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