QA Automation Engineer (DevOps) - Unified Communications & Contact Center Platforms

Job Description About the Platform This role supports Contact Center as a Service (CCaaS) — a cloud-native, AI-driven customer experience platform delivering omnichannel customer engagement, intelligent routing, conversational AI, workforce optimization, analytics, and agent desktop capabilities. The platform follows an Agile/Scrum delivery model, with fast-paced delivery, frequent releases, and CI/CD deployment pipelines. About the Role We are seeking highly skilled Platform/DevOps Senior QA engineers to drive quality engineering for Unified Communications (UC) and Contact Center platforms. This role focuses on validating delivery and runtime behavior for DevOps-led changes across CI/CD, deployments, shared environments, platform integrations, and service reliability. Engineers will own automation strategy, release quality evidence, deployment validation, and runtime assurance in partnership with Platform, DevOps, Cloud, and Product Engineering teams. The ideal candidate brings strong automation engineering expertise, critical system-thinking, and hands-on experience validating cloud-native deployments, APIs, platform integrations, and operational readiness in large-scale enterprise communication ecosystems. Responsibilities Design, develop, and maintain automated validation frameworks for DevOps delivery flows, including build validation, artifact verification, deployment validation, smoke/health testing, rollback testing, and release readiness. Validate Kubernetes-backed deployments for Unified Communications and Contact Center workloads, including rollout status, readiness/liveness behavior, ingress, service exposure, pod health, and runtime observability. Integrate automated validation suites into CI/CD pipelines such as GitHub Actions, Jenkins, and Azure DevOps to enable continuous quality gates. Validate end-to-end service integrations across communication workflows, APIs, platform services, identity systems, and dependent microservices. Analyze and triage failures across pipeline logs, deployment metadata, Kubernetes events, and runtime logs to identify defects affecting delivery stability and cross-team integration. Own automation coverage strategy, quality gates, test cataloging, and exit criteria for DevOps-led platform changes. Reduce test instability by identifying flaky automation patterns and improving reliability, diagnostics, and repeatability. Validate REST APIs, JSON/YAML payloads, service contracts, and integration points for UC and Contact Center capabilities. Document environment dependencies, limitations, validation evidence, release readiness metrics, and defect impact assessments. Collaborate with Platform Engineering, DevOps, SRE, Cloud, and Product teams to improve delivery quality, deployment confidence, and operational resilience. Looking For 6-8 years of experience in QA Automation, SDET, Software Test Engineering, or Platform Validation roles. Mandatory Skills: A. Technical Skills Strong programming expertise in Python, TypeScript, Java, or C# with solid Git/Git workflow experience. Hands-on experience integrating automation into CI/CD systems such as GitHub Actions, Jenkins, or Azure DevOps. Strong Kubernetes validation experience, including kubectl usage, rollout verification, pod inspection, log analysis, service troubleshooting, readiness/liveness validation, and deployment debugging. Hands-on experience validating containers, REST APIs, JSON/YAML payloads, and distributed platform integrations. Cloud validation experience with Azure and GCP, including environment validation and deployment verification. Strong troubleshooting skills with the ability to analyze failures across logs, deployment metadata, and integration paths. Experience defining automation coverage, release exit criteria, and quality evidence for production readiness. B. Soft Skills Strong critical thinking and system-level troubleshooting skills Automation-first quality mindset High ownership and accountability for release quality Cross-functional collaboration across DevOps, Platform, Cloud, and Engineering teams Strong analytical and debugging capabilities in complex distributed systems Good to Have Skills: Exposure to managed Kubernetes platforms such as AKS and GKE. Experience validating GitOps workflows (Argo CD) and Infrastructure as Code (Terraform/Ansible) from a QA or validation perspective. Knowledge of OAuth2/OIDC authentication and Keycloak integration testing. Scripting proficiency in PowerShell and/or Bash for validation, diagnostics, and automation. Experience testing Unified Communications, Contact Center, VoIP, SIP, media services, routing, call flows, integrations, or enterprise communication systems. Understanding of distributed systems, observability, deployment resiliency, and production-quality validation. Qualifications Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field. Company Description Engineering the AI-powered enterprise. With AI and