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Job Description
5+ years of experience in QA automation, including at least 3 years writing automated tests in Python
Strong hands-on experience with pytest (fixtures, parametrization, plugins, markers) and building automation frameworks from scratch
Solid experience in REST API testing (requests/httpx, schema and contract validation)
Experience testing distributed, event-driven backend systems (message queues, async processing, eventual consistency)
Practical knowledge of AWS services such as S3, SQS/SNS, EventBridge, Lambda, DynamoDB and RDS/Aurora, and of testing against them with boto3 and LocalStack or moto
Good SQL skills for data validation (PostgreSQL/Aurora)
Experience integrating test suites into CI/CD pipelines, preferably Azure DevOps, including reporting (Allure or similar) and quality gates
Working knowledge of Docker and Git
Understanding of test design techniques, test pyramid principles and risk-based testing
Upper-Intermediate English or higher, spoken and written
Nice to have:
Experience in regulated domains such as medical devices, healthcare or pharma (IEC 62304, FDA, GxP, ISO 13485), including requirements traceability and validation documentation
Experience testing IoT or connected-device platforms (device provisioning, certificates, TLS/mTLS, OTA updates)
Experience testing data and log-processing pipelines (file parsing, CSV/data validation, large datasets)
Exposure to testing LLM-based or agentic AI applications (LangChain/LangGraph, AWS Bedrock, evaluation of model outputs)
Performance or load testing (Locust, k6)
Basic Java reading skills, since the core backend services are written in Java
AWS or ISTQB certification
Job Responsibilities
Design, build and maintain a Python-based test automation framework for a cloud platform that manages connected medical devices
Develop automated API, integration and end-to-end tests covering device management, log processing, content delivery, remote access and security flows
Automate validation of log-parsing pipelines and the data they produce
Build and run tests against AWS services, using LocalStack for local and pipeline environments
Integrate automated suites into Azure DevOps CI/CD pipelines and maintain stable, fast regression and smoke runs
Take ownership of regression and smoke suite execution during and after the platform handover from the previous vendor
Contribute to quality of the new AI analytics layer, including test strategies for natural-language queries and validation of generated results
Report, triage and track defects, and take part in root-cause analysis together with developers
Maintain test documentation and traceability between requirements and tests, in line with regulated SDLC and compliance needs
Work closely with the developers, DevOps and the Business Analyst in an Agile team
Department/Project Description
Our client is a global leader in eye-care medical devices. We are taking full engineering ownership of their Service Cloud: an AWS-based platform that connects thousands of surgical and diagnostic devices worldwide. The platform handles the full device lifecycle, from secure provisioning and certificate-based onboarding to log collection and parsing, software updates, remote support and audit logging.
The project combines three workstreams in one team: Service Cloud engineering and L3/L4 support, log parser development, and cloud and AI modernization. The modernization starts with a conversational analytics layer, where users ask questions in plain language and an AI agent builds queries and dashboards over device and log data.
You'll join a cross-functional team of architects, Java, C++, AI/ML and DevOps engineers. You'll help shape the quality approach for a live, regulated medical-device platform at a point where the team is taking it over and setting its standards.

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