Senior DevOps Engineer

We are looking for a senior, hands-on platform engineer to own the reliability, security and operational maturity of our Azure and Kubernetes platform. You will work within our platform team, in partnership with the DevOps Team Lead, architecture, engineering, cybersecurity and data/ML teams, to build secure-by-default cloud infrastructure and support the safe operation of emerging AI workloads.

In this role, you will directly influence uptime, performance, cloud security posture and customer experience on Azure. You will also help define how the organization safely runs AI-enabled workloads in production, while evolving the engineering culture toward reliability-first, security-by-default, cloud-native delivery.

Essential Duties and Responsibilities

1. Azure, AKS and platform reliability

• Design, build and operate secure, highly available Azure cloud architecture for microservices, event-driven systems and AI-related workloads.
• Define and improve SLIs, SLOs, error budgets, resilience patterns and operational standards for production services.

2. Kubernetes platform engineering and automation

• Operate production and non-production AKS clusters, including node pools, upgrades, autoscaling, RBAC, network policies, resource quotas and isolation patterns.
• Automate provisioning and lifecycle management using Infrastructure as Code, GitOps, Helm and Kustomize.

3. Platform security and DevSecOps

• Own Azure and AKS security posture across identity, networking, secrets, policy, vulnerability management and software supply chain controls.
• Embed security into CI/CD pipelines through scanning, policy-as-code, deployment gates, audit logging and automated response pattern

4. API gateways, ingress and service traffic

• Design and operate Kubernetes API gateway and ingress layers, ideally using Apache APISIX or a similar platform such as Kong.
• Implement routing, load balancing, rate limiting, OAuth2/OIDC, JWT, mTLS, traffic controls and API lifecycle standards.

5. Observability, incidents and operational excellence

• Build meaningful metrics, logs, traces, dashboards and alerts using Azure Monitor, Application Insights, Log Analytics, Prometheus, Grafana and OpenTelemetry.
• Lead or support incident response, root cause analysis, runbooks, reliability improvements, chaos testing and on-call readiness.

6. Safe AI/LLM workload operations on Kubernetes

• Support secure deployment and governance of AI, LLM or agentic workloads using controlled identities, network isolation, auditing, resource limits and approval gates.
• Partner with data/ML and security teams to reduce risks such as prompt injection, tool abuse, data exfiltration and uncontrolled compute spend.

7. Technical leadership and enablement

• Partner with engineering teams to define platform standards, coach teams on secure-by-default practices and improve developer self-service.
• Create and maintain documentation, runbooks, threat models and reusable automation that reduce operational toil.

Required skills and experience

Must-haves

• 5+ years in DevOps, SRE, Platform, Cloud or Infrastructure Engineering roles with significant production ownership.
• Deep hands-on Azure experience, especially AKS, Azure Networking, Entra ID, Azure Policy, Azure Monitor, Application Insights, Log Analytics and Azure DevOps.
• Strong AKS and Kubernetes experience, including cluster and node pool design, CNI/networking, private clusters, DNS, ingress, RBAC, Managed Identities and autoscaling.
• Strong infrastructure security background on Azure: Defender for Cloud, Microsoft Sentinel or SIEM/SOAR, Zero Trust, least privilege, network hardening, secrets management and supply chain security.
• Infrastructure as Code and configuration management experience with Terraform, Bicep or Pulumi, plus Helm and/or Kustomize.
• CI/CD and DevSecOps experience, ideally with Azure DevOps Pipelines, including SAST/DAST, dependency or image scanning, IaC scanning, secret detection and deployment gates.
• Observability and incident management experience across metrics, logs, traces, alerting, SLOs/SLIs, root cause analysis and durable remediation.
• Strong scripting or programming ability in Python, Bash, PowerShell and/or Go.
• Practical experience with Kubernetes API gateways or ingress platforms, such as Apache APISIX, Kong or similar.

Required skills and experience

Nice-to-haves

• Experience deploying or governing AI, LLM or agentic workloads on Kubernetes, including inference serving, tool gateways or MCP servers, guardrails, sandboxing, agent identity and behavioral observability.
• Relevant certifications such as CKA, CKS, AZ-104, AZ-400, AZ-500, AZ-305, SC-100 or equivalent.
• Service mesh experience with Istio, Linkerd or Cilium for traffic management, observability and mTLS.
• GitOps experience with Argo CD or Flux.
• Experience with event-driven systems such as Kafka, Azure Event Hubs, Azure Service Bus or RabbitMQ.
• Experience with multi-cluster or hybrid-cloud Kubernetes, chaos engineering, resilience testing or FinOps/cost governance on Azure.
• Performance tuning experience for high-throughput APIs, event-processing platforms or Kubernetes workloads.

What will help you succeed

• A calm, structured approach during high-pressure incidents, including security events.
• A security-first mindset with the ability to balance reliability, delivery speed and risk.
• Clear communication skills and the ability to simplify complex technical topics for different audiences.
• A collaborative, ownership-driven style: you work well in a platform team, share knowledge openly and can take a problem from architecture through production operation.