SME - Azure DevOps, Terraform
Confirmed on the employer's own hiring board on Nov 8, 2026. First seen by Alion on Nov 4, 2026.
Job Summary
Key Responsibilities Design and execute resiliency and chaos testing scenarios across cloud, Kubernetes, APIs, microservices, and distributed environments. AWS FIS knowledge, setup and Run Experiments AWS CDK knowledge. Identify resilience gaps, SPOFs, and operational risks and drive remediation. Validate High Availability (HA), Disaster Recovery (DR), failover, auto-healing, and recovery processes. Automate testing and reliability validation using scripting and cloud-native tools. Monitor application and infrastructure behavior using observability platforms such as AppDynamics, Prometheus, and Grafana. Collaborate with DevOps, SRE, Infrastructure, and Application teams to improve system reliability. Define and track reliability metrics including SLA, SLO, SLI, MTTR, RTO, and RPO. Required Skills Strong experience in Java/Python, Microservices, APIs, Kubernetes, Docker, and Cloud Platforms (Azure/GCP/AWS). Hands-on experience with monitoring and observability tools such as Dynatrace metrics and observability, AppDynamics, Prometheus, and Grafana. Knowledge of Reliability Engineering, Chaos Testing, Incident Analysis, and Resiliency Validation. Failure-as-a-Service platforms to achieve resiliency in infrastructure failures, network and application failures. Chaos Testing mechanism and tools such as AWS-FIS, Lambda testing, On-premise , OpenShift testing. Monitoring tools test/scenario capture and report creation through standardized templates and hypothesis formation. Experience with automation, CI/CD, and cloud-native architectures. Excellent troubleshooting, analytical, and communication skills.
Key Responsibilities
Key Responsibilities Design and execute resiliency and chaos testing scenarios across cloud, Kubernetes, APIs, microservices, and distributed environments. AWS FIS knowledge, setup and Run Experiments AWS CDK knowledge. Identify resilience gaps, SPOFs, and operational risks and drive remediation. Validate High Availability (HA), Disaster Recovery (DR), failover, auto-healing, and recovery processes. Automate testing and reliability validation using scripting and cloud-native tools. Monitor application and infrastructure behavior using observability platforms such as AppDynamics, Prometheus, and Grafana. Collaborate with DevOps, SRE, Infrastructure, and Application teams to improve system reliability. Define and track reliability metrics including SLA, SLO, SLI, MTTR, RTO, and RPO. Required Skills Strong experience in Java/Python, Microservices, APIs, Kubernetes, Docker, and Cloud Platforms (Azure/GCP/AWS). Hands-on experience with monitoring and observability tools such as Dynatrace metrics and observability, AppDynamics, Prometheus, and Grafana. Knowledge of Reliability Engineering, Chaos Testing, Incident Analysis, and Resiliency Validation. Failure-as-a-Service platforms to achieve resiliency in infrastructure failures, network and application failures. Chaos Testing mechanism and tools such as AWS-FIS, Lambda testing, On-premise , OpenShift testing. Monitoring tools test/scenario capture and report creation through standardized templates and hypothesis formation. Experience with automation, CI/CD, and cloud-native architectures. Excellent troubleshooting, analytical, and communication skills.
Skill Requirements
Key Responsibilities Design and execute resiliency and chaos testing scenarios across cloud, Kubernetes, APIs, microservices, and distributed environments. AWS FIS knowledge, setup and Run Experiments AWS CDK knowledge. Identify resilience gaps, SPOFs, and operational risks and drive remediation. Validate High Availability (HA), Disaster Recovery (DR), failover, auto-healing, and recovery processes. Automate testing and reliability validation using scripting and cloud-native tools. Monitor application and infrastructure behavior using observability platforms such as AppDynamics, Prometheus, and Grafana. Collaborate with DevOps, SRE, Infrastructure, and Application teams to improve system reliability. Define and track reliability metrics including SLA, SLO, SLI, MTTR, RTO, and RPO. Required Skills Strong experience in Java/Python, Microservices, APIs, Kubernetes, Docker, and Cloud Platforms (Azure/GCP/AWS). Hands-on experience with monitoring and observability tools such as Dynatrace metrics and observability, AppDynamics, Prometheus, and Grafana. Knowledge of Reliability Engineering, Chaos Testing, Incident Analysis, and Resiliency Validation. Failure-as-a-Service platforms to achieve resiliency in infrastructure failures, network and application failures. Chaos Testing mechanism and tools such as AWS-FIS, Lambda testing, On-premise , OpenShift testing. Monitoring tools test/scenario capture and report creation through standardized templates and hypothesis formation. Experience with automation, CI/CD, and cloud-native architectures. Excellent troubleshooting, analytical, and communication skills.
Other Requirements
Key Responsibilities Design and execute resiliency and chaos testing scenarios across cloud, Kubernetes, APIs, microservices, and distributed environments. AWS FIS knowledge, setup and Run Experiments AWS CDK knowledge. Identify resilience gaps, SPOFs, and operational risks and drive remediation. Validate High Availability (HA), Disaster Recovery (DR), failover, auto-healing, and recovery processes. Automate testing and reliability validation using scripting and cloud-native tools. Monitor application and infrastructure behavior using observability platforms such as AppDynamics, Prometheus, and Grafana. Collaborate with DevOps, SRE, Infrastructure, and Application teams to improve system reliability. Define and track reliability metrics including SLA, SLO, SLI, MTTR, RTO, and RPO. Required Skills Strong experience in Java/Python, Microservices, APIs, Kubernetes, Docker, and Cloud Platforms (Azure/GCP/AWS). Hands-on experience with monitoring and observability tools such as Dynatrace metrics and observability, AppDynamics, Prometheus, and Grafana. Knowledge of Reliability Engineering, Chaos Testing, Incident Analysis, and Resiliency Validation. Failure-as-a-Service platforms to achieve resiliency in infrastructure failures, network and application failures. Chaos Testing mechanism and tools such as AWS-FIS, Lambda testing, On-premise , OpenShift testing. Monitoring tools test/scenario capture and report creation through standardized templates and hypothesis formation. Experience with automation, CI/CD, and cloud-native architectures. Excellent troubleshooting, analytical, and communication skills.