Key Responsibilities

• Design, develop, maintain, and document production-grade automation frameworks, reusable Python packages, fixtures, command-line tools, test utilities, and supporting services.
• Use AI-assisted development tools in day-to-day engineering to accelerate coding, refactoring, test generation, debugging, analysis, and documentation while independently reviewing outputs for correctness, security, maintainability, and licensing risk.
• Design automated tests with Pytest and apply deep knowledge of collection and execution flow, fixtures, parametrization, markers, hooks, configuration, and plugin architecture.
• Configure, extend, or create Pytest plugins for parallel execution, reporting, retries, logging, test selection, resource coordination, port allocation, environment management, and CI-friendly result publication.
• Read and understand existing Java code and create or modify small Java scripts or utilities when required. The role does not own Java-based test automation.
• Develop, integrate, and validate REST APIs and gRPC services, including unary calls, server-side streaming, client-side streaming where applicable, and bi-directional streaming.
• Build automation for distributed, event-driven microservices and asynchronous workflows using Azure Service Bus and Azure Blob Storage, including message correlation, ordering, timing, retries, idempotency, dead-letter handling, failure recovery, and data validation.
• Create functional, integration, component, contract, system, regression, reliability, resilience, performance, and scalability automation for service-based and end-to-end workflows.
• Validate distributed-system behaviours such as eventual consistency, partial failure, timeout propagation, retry behaviour, duplicate delivery, backpressure, concurrency, and service recovery.
• Integrate tests, reports, logs, artifacts, environment controls, and automated quality gates into GitLab CI/CD pipelines and GitLab Runner environments.
• Package and execute automation in containerized environments and deploy, inspect, diagnose, and troubleshoot tests and microservices running on Kubernetes.
• Improve repeatability through deterministic test data, configuration management, environment isolation, structured logging, metrics, traces, and actionable failure diagnostics.
• Participate in code reviews, technical design discussions, engineering standards, documentation, and peer knowledge sharing as a senior individual contributor.