Platform Engineer

Implement and operate Kubernetes infrastructure (AKS): cluster lifecycle, networking, resource management, auto-scaling, and multi-tenancy patterns. - Build and maintain CI/CD pipelines using GitHub Actions and ArgoCD for automated testing, container builds, and GitOps deployments. - Develop Infrastructure as Code (Terraform, Bicep) to provision and manage Azure resources with consistency and auditability. - Operate container registries (ACR), artifact management, and image security scanning workflows. - Implement and maintain observability infrastructure: Azure Monitor, Application Insights, Prometheus, Grafana-including dashboards, alerting, and distributed tracing. - Manage async processing infrastructure: Celery workers, Redis queues, and workflow orchestration patterns supporting AI agent execution. - Implement platform security controls: network policies, pod security standards, Key Vault integration, RBAC, and private endpoint configurations. - Support database

infrastructure: PostgreSQL management, backup/recovery, connection pooling, and performance tuning. - Create self-service tooling and templates that enable development teams to deploy and operate services with minimal friction. - Diagnose and resolve infrastructure issues across clusters, pipelines, and cloud services; perform root-cause analysis and implement preventative improvements. - Collaborate with Platform Architects, Backend Engineers, and ML Engineers to translate architecture designs into reliable infrastructure. What You Bring - 5+ years professional experience in platform engineering, SRE, or DevOps roles; experience supporting AI/ML workloads is a strong plus. - Strong Kubernetes experience: cluster operations, networking (Ingress, network policies), storage, autoscaling, and troubleshooting. - Solid Infrastructure as Code experience with Terraform, Bicep, or equivalent tools. - Production experience with Azure cloud services: AKS, ACR, Key Vault, Azure Monitor, Virtual Networks, Private Endpoints, and Azure Policy. - Strong CI/CD experience: GitHub Actions (self-hosted runners, reusable workflows), ArgoCD, or similar GitOps tooling. - Proficiency in Python for automation, scripting, and tooling. - Experience with container security: image scanning, runtime security, network policies, and least-privilege patterns. - Experience with observability stack: Prometheus, Grafana, centralized logging, and alerting configuration. - Familiarity with async task processing: Celery, Redis, or equivalent message queue patterns. - Strong Linux systems administration and networking fundamentals. - Operational mindset with strong troubleshooting skills across infrastructure layers. Ways of Working - Comfortable in agile, iterative delivery environments with ownership and accountability. - Clear communicator and collaborator across global, cross-functional stakeholders. - Strong focus on reliability and automation: you measure success by system uptime and reduced manual toil. - Proactive learner with pragmatic adoption of AI-assisted developer tools (GitHub Copilot, Claude Code) to improve automation and delivery. Nice to Have - Experience supporting AI/ML infrastructure: GPU scheduling, model serving platforms, or ML pipeline orchestration. - Service mesh experience (Istio, Linkerd) for traffic management and security. - Experience with Databricks or similar data platform infrastructure. - Familiarity with workflow orchestration (Temporal, Airflow) for complex AI pipelines. - Experience with cost optimization: FinOps practices, reso