🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Cookies & analytics consent
We serve candidates globally, so we only activate Google Tag Manager and other analytics after you opt in. This keeps us aligned with GDPR/UK DPA, ePrivacy, LGPD, and similar rules. Essential features still run without analytics cookies.
Read how we use data in our Privacy Policy and Terms of Service.
🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
inDrive • Astana, Kazakhstan
Role & seniority: Senior QA Engineer, AI Solutions Delivery, Full Time
Stack/tools: Python, Pytest, Linux/Bash; Docker, Kubernetes, basic CI/CD; API testing (REST/gRPC); SQL; Kafka, Kibana; Open Lens; bug-tracking systems; microservices
Test backend services across the product lifecycle; analyze results and identify issues
Develop/maintain test plans, test cases, and automated API tests
Perform regression testing; document/track bugs; collaborate with cross-functional teams to improve QA processes
3+ years backend QA/testing experience
Proficiency with Pytest and Python
Linux/Bash scripting; Docker/Kubernetes basics; basic CI/CD
RESTful and gRPC API testing; SQL
Understanding of client/server and microservices; strong team collaboration; willingness to learn ML basics
Kafka, Kibana experience; familiarity with Open Lens
Experience with AI/ML workflow testing or exposure to ML concepts
Location & work type: Kazakhstan, Hybrid work mode, Flexible schedule; relocation package available for other regions
Senior QA Engineer
Department: AI Cluster
Employment Type: Full Time
Location: Kazakhstan
Description We’re looking for a QA to join the AI Solutions Delivery team. The team is responsible for the development and implementation of AI solutions, currently focusing on automation in Customer Support — including first-line support, driver verification, and content moderation. Our goal is to deliver reliable, scalable AI-driven tools that streamline operations and improve user experience. As a QA, you’ll be working with backend-heavy services, primarily testing APIs using Python and Pytest. We put strong emphasis on test coverage and automation, ensuring the robustness of AI systems integrated into complex business workflows.
Key Responsibilities Actively participate in all stages of the product lifecycle, from initial concept through to deployment Test backend services, analyze results, and identify issues Develop and maintain test plans, test cases, and documentation for applications Write API automated tests using Pytest or other relevant tools Identify, document, and track bugs and issues using a bug tracking system. Collaborate with cross functional teams to understand project requirements and clarify ambiguities Perform regression testing to ensure product stability after new changes Collaborate with TechOps and other teams to implement quality management processes and improve testing
Skills, Knowledge and Expertise 3 or more years of experience in QA, predominantly with backend testing. Proficient in Pytest and Python for writing test scripts. Proficient in working with Linux and related tools; solid knowledge of Bash scripting. Understanding of Docker, Kubernetes principles, basic CI CD knowledge, and the ability to analyse backend service logs, including using Open Lens or similar tools. Experience with Kafka and Kibana or a willingness to quickly learn them. Skilled in testing RESTful and gRPC APIs. Basic proficiency in SQL. Good understanding of client server and microservice architecture. Ability to work in a team. Familiarity with the basics of Machine Learning or a willingness to learn.
Conditions & Benefits Stable salary, official employment Health insurance Hybrid work mode and flexible schedule Relocation package offered for candidates from other regions Access to professional counseling services including psychological, financial, and legal support Discount club membership Diverse internal training programs Partially or fully paid additional training courses All necessary work equipment