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Senior Automation Quality Engineer (Python)
What the posting is about
Senior Automation Quality Engineer with 6+ years of experience in test automation using Python. Proficient in Playwright, PyTest, and BDD/Gherkin. Skilled in AI coding assistants and prompt engineering. Responsible for reviewing AI-generated test scenarios and automation code, building Python-based automation frameworks, and maintaining test coverage. Committed to creating a respectful work environment with equal opportunities.
Read out of the posting
Levelsenior
Experience asked6+ years
EmploymentFull time
LocationOhrid, South-Eastern Europe, MK, Skopje, Bitola, Beograd, RS, Kragujevac, Niš, Novi Sad
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-08-18
Found viateamtailor, direct from their system
We saw it 2 months after it went up.
The posting, as the company wrote it
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.
Copied from Avenga’s own board, not rewritten. Original ↗
Also open at Avenga
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