Platform Test Engineer

Company Description CloudPi is a governed FinOps platform built to help enterprises control, automate, and verify cloud cost savings across AWS, Azure, and GCP. The platform delivers accurate cost allocation from day one, without lengthy tagging projects or complex setup, achieving 85%+ allocation as soon as cloud accounts are connected. CloudPi's Intelligent Savings engine combines automated workflows, gated controls, and rollback safety to execute savings while keeping teams in full control. Every dollar saved on CloudPi is auditable and verifiable, providing trustworthy data for technical and executive stakeholders. CloudPi is designed for organizations that need a single, unified source of truth for cloud spend and cannot afford to make mistakes in cloud financial management.

We are seeking a highly skilled Platform Test Engineer to join the CloudPi team. In this role, you will be responsible for ensuring the reliability, performance, and security of our multi-cloud management platform. You will design and execute sophisticated testing strategies that validate our core infrastructure, AI-powered cost optimization engines, and seamless integrations across AWS, GCP, and Azure.

Key Responsibilities

• Conduct end-to-end platform validation for the CloudPi platform, covering multi-cloud orchestration workflows, API integrity, tenant lifecycle management, and workspace provisioning.
• Design, develop, and maintain scalable automation frameworks using Python, Java, or Go to validate cloud-native applications, distributed systems, and microservices architectures.
• Create and execute automated test suites for REST APIs, asynchronous services, containerized workloads, and orchestration layers across AWS, Azure, and GCP environments.
• Validate Infrastructure-as-Code (IaC) deployments using Terraform and CloudFormation to ensure infrastructure consistency, workspace isolation, policy enforcement, and deployment reliability.
• Perform performance, load, stress, endurance, and concurrency testing to validate platform scalability, resilience, and 99.99% uptime objectives under enterprise-scale workloads.
• Develop automated regression pipelines integrated with CI/CD systems such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps to enable continuous quality validation.
• Conduct security and compliance testing, including vulnerability assessments, RBAC validation, access control verification, secrets management testing, and data localization compliance checks.
• Collaborate closely with DevOps, SRE, Platform Engineering, and Product teams to implement shift-left testing strategies and accelerate release quality.
• Monitor platform stability through log analysis, observability tools, distributed tracing, and cloud monitoring solutions to identify bottlenecks and production risks proactively.
• Build reusable testing utilities, mocks, simulators, and cloud environment validation tools to improve automation coverage and execution efficiency.
• Validate Kubernetes-based deployments, container orchestration workflows, autoscaling policies, service mesh integrations, and cloud networking configurations.
• Participate in root cause analysis, defect triaging, and incident validation to ensure rapid issue resolution and platform reliability.
• Maintain detailed test documentation, automation reports, quality metrics, and release readiness dashboards for enterprise stakeholders.
• Ensure platform releases meet enterprise-grade standards for scalability, security, availability, reliability, and operational excellence.

Technical Requirements

10+ years of experience in Software Quality Engineering, with a minimum of 3 years focused on Cloud Platform Testing and cloud-native application validation.

Strong hands-on expertise with at least two major cloud platforms, including AWS, Azure, or GCP, covering infrastructure, networking, security, and cloud service validation.

Proficiency in automation testing frameworks and tools such as Selenium, Cypress, Playwright, and Postman for UI, API, and end-to-end testing.

Extensive experience in API testing, contract validation, and microservices testing using REST, GraphQL, and event-driven architectures.

Strong understanding of cloud-native architectures, including Microservices, Kubernetes (K8s), Docker, container orchestration, and serverless computing models.

Experience validating Kubernetes workloads, Helm deployments, autoscaling, ingress configurations, and distributed cloud services.

Expertise in building scalable automation frameworks using Python, Java, or Go for enterprise-grade cloud platforms.

Hands-on experience with CI/CD pipelines, DevOps workflows, and test automation integration using Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.

Solid understanding of Infrastructure-as-Code (IaC) technologies such as Terraform and CloudFormation, including automated validation and deployment testing.

Experience performing performance, scalability, load, and stress testing for highly available distributed systems and cloud environments.

Strong knowledge of cloud security testing, RBAC validation, IAM policies, vulnerability assessment, and compliance testing methodologies.

Experience testing data-intensive platforms, particularly applications related to cloud cost optimization, FinOps analytics, billing systems, or usage metering platforms.

Familiarity with observability and monitoring tools such as Prometheus, Grafana, ELK Stack, Datadog, or CloudWatch for platform validation and diagnostics.

Strong analytical, debugging, and root cause analysis skills for identifying complex platform and infrastructure issues.

Excellent collaboration and communication skills, with experience working closely with DevOps, SRE, Engineering, and Product teams in Agile environments.

Preferred Qualifications

 * Experience with FinOps principles or cloud cost optimization tools.

 * Background in testing AI/ML-driven insights or automated workflow engines.

 * Relevant certifications (e.g., AWS Certified SysOps Administrator, Azure Solutions Architect, or CSTE/ISTQB).