Software Technical Lead Engineer

Design, develop, and maintain automated test scripts using PyTest with structured Allure reporting Leverage GitHub Copilot to write and execute Python-based test automation for software validation across functional, regression, and sanity test cycles. Apply prompt engineering techniques to interact with AI/LLM tools for test case generation, failure analysis, and QA reporting. Contribute to AI agent design \u2014 build or integrate agents that automate repetitive QA workflows (e.g., PR analysis, release note generation, test coverage mapping). Leverage GitHub Copilot within VS Code to accelerate test authoring, code review, and documentation generation. Explore and implement MCP (Model Context Protocol)-based integrations to connect AI agents with internal tools, simulators, and test infrastructure. Collaborate with development and QA leads to improve test coverage, traceability, and evidence quality across releases. ELIGIBILITY CRITERIA Bachelor\u0027s degree in engineering preferably Computer Sc / Electronics / Information Technology Years of Experience - 3-7 years Python Basics \u2014 Comfortable writing functions, classes, and scripts for test automation. PyTest + Allure \u2014 Experience writing structured test cases with fixtures, markers, and generating Allure evidence reports. VS Code + GitHub Copilot \u2014 Proficient in AI-assisted development workflows; knows how to review, refine, and validate Copilot suggestions. Prompt Engineering \u2014 Ability to craft effective prompts for code generation, test case creation, and QA analysis using LLMs (ChatGPT, Copilot, etc.). Agent Design \u0026 MCP Basics \u2014 Familiarity with AI agent concepts; exposure to MCP tools or willingness to learn how agents interact with external systems via protocols. Experience with Allure test evidence packs (step-by-step logs, event context, screenshots). Exposure to Jira / Bitbucket for test management and traceability. Understanding of Git workflows (branching, PRs, code reviews). Interest in GenAI adoption in QA \u2014 test intelligence, auto-triage, AI-driven coverage analysis