Senior Automation Quality Engineer (Python)
Avenga Bitola, North Macedonia
IT Services and IT Consulting · 5,001-10,000 employees
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About the role
The engineer will review AI-generated test scenarios and automation code to ensure quality and correctness before implementation. They will also build and maintain Python-based automation frameworks while designing UI, API, and database test coverage.
What they look for
Requirements
Candidates must have 6+ years of hands-on test automation experience with strong proficiency in Python and Playwright. A solid understanding of AI agentic systems, prompt engineering, and LLM concepts is required for this role.
Full description
Avenga is an international engineering firm helping businesses operate with AI at the core. With 6,000+ experts worldwide, we combine engineering expertise with AI-native thinking to turn ambitious ideas into real-world impact across industries, technologies, and markets.
Core skills you’ll bring
- 6+ years of hands-on test automation experience, with strong working knowledge of Python
- Experience with Playwright for UI automation
- Experience with PyTest or a similar framework for API test automation
- Familiarity with BDD/Gherkin (Behave or similar) - able to read, critique, and extend feature files
- Working SQL skills and comfort validating data directly against a database
- Solid Git/GitHub experience, including pull-request-based review workflows
AI & Agentic skills:
- Hands-on experience with AI coding assistants (GitHub Copilot, Claude, Cursor, or similar) in a real development or test-automation workflow - not just occasional chat-interface use
- Practical understanding of agentic AI systems: multiple AI agents with defined roles collaborating on a task (e.g., one agent drafting, another reviewing), and how orchestration/handoffs between them work
- Working knowledge of prompt engineering - able to write and refine prompts/instructions that reliably shape an AI agent's output, not just ask ad hoc questions
- Understanding of core LLM concepts relevant to daily work: context windows, hallucination, retrieval-augmented generation (RAG), and why these create the need for human review
- Exposure to agent frameworks or tooling is a strong plus - e.g., LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), or Copilot/Claude agent extensions
The impact you'll create
- Review AI-generated test scenarios for coverage, correctness, and missing edge cases before implementation begins
- Review AI-generated automation code for quality and correctness before it is merged, acting as the final human checkpoint
- Write and refine the instructions, prompts, and context files that shape how AI agents behave for a given application or task
- Build and maintain Python-based automation frameworks — page objects/clients, step definitions, fixtures, and test data
- Design and maintain UI, API, and database test coverage using Playwright, PyTest, and SQL-based validation
- Triage self-healing suggestions on flaky or broken tests — approve, reject, or fix them directly
- Help onboard new applications into the automation framework, mapping existing tests and domain conventions
- Track coverage, regression health, and quality metrics, and report on them to the delivery team
People are at the core of Avenga. We provide equal opportunities regardless of race, ethnicity, gender identity, sexual orientation, disability, age, religion, or any other characteristic. We are committed to a respectful environment where everyone can be themselves, share their ideas, and feel that they belong.
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