Senior Platform Engineer with 6+ years of cloud infrastructure experience at Wagepoint. Designing Azure and managing Kubernetes for a reliable payroll SaaS platform.
About the role
- Associate Platform Engineer enabling secure, scalable Azure and Google Cloud AI/ML capabilities. Collaborating with teams to build Infrastructure as Code and automated testing frameworks.
Responsibilities
- Help with end-to-end delivery of Infrastructure as Code for cloud AI services
- Design platform abstractions that let application teams self-serve safely
- Embed security and compliance into the platform
- Build patterns for safe consumption of generative AI
Requirements
- 1+ years of cloud platform or infrastructure engineering experience
- Terraform - module design, composition, workspaces, testing, drift management, and pipeline patterns
- Python for platform work: SDK integrations, CLI/tooling, automated testing, packaging, observability hooks
- Experience with GitHub Actions (or comparable CI/CD) including reusable workflows, environments, OIDC-based cloud auth, deployment gating, and secret management
- Demonstrable experience deploying and operating AI/ML services on Azure (Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Bot Service, Azure ML) and/or Google Cloud (Vertex AI, BigQuery, Pub/Sub)
- Hands-on understanding of cloud networking at depth: VNets/VPCs, NSGs/firewall rules, hub-spoke and shared VPC patterns, private endpoints, ExpressRoute, DNS, and routing across hybrid topologies
- Security engineering instincts: RBAC/IAM design, identity federation (Azure AD/Entra, Google Cloud Identity, AD, PingFederate), Key Vault / Secret Manager, PKI and certificate lifecycle, data protection, and policy-as-code.
Benefits
- Base salary
- Variable compensation
- Health and well-being benefits
- Savings and retirement programs
- Paid time off
- Banking benefits and discounts
- Career development
- Reward and recognition programs
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