
Cloud Engineer
2 days ago
About Us
We're developing a cutting-edge, multi-tenant AI governance platform on Microsoft Azure.
Key Responsibilities:- Design and Build Cloud Services: Design, build, and implement secure, scalable cloud services on Azure; integrate Azure ML Responsible AI tooling and Microsoft Purview to enforce policy guardrails with Azure Policy.
- Integrate Azure Services: Integrate Azure ML (model registry/endpoints) and Responsible AI Dashboard/Toolbox for generating fairness, error, and explainability reports.
- Azure AI Governance: Implement Azure AI Content Safety checks in the prompt/response path to ensure data integrity and security.
- Data Lineage and Compliance: Connect datasets, prompts/outputs, and lineage to Microsoft Purview for enhanced transparency and audit/reporting workflows.
- Azure Policy Enforcement: Enforce Azure Policy baselines (networking, encryption, diagnostics), Infrastructure as Code (IAC) for repeatable deployments.
- Observability and Security: Build observability (App Insights/Log Analytics), service level objectives (SLOs), alerting, and secure secret management (Key Vault).
- Collaboration: Collaborate with Product and Compliance teams on governance features, such as access reviews, approvals, and audit exports.
Requirements:
- 5+ years of experience building cloud services 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:
- 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.
Success Metrics in 90 Days:
- Deploy a secure tenant onboarding flow (RBAC + data partitioning).
- Set up APIM + first governance microservice with Content Safety checks.
- Register a sample model in Azure ML, attach Responsible AI reports, and stream lineage to Purview.
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