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Software Technical Lead Engineer

Lam Research · Bengaluru

Information Technology Software & Development Full-time Posted 4 days ago

About this role

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 — 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's degree in engineering preferably Computer Sc / Electronics / Information Technology Years of Experience - 3-7 years Python Basics — Comfortable writing functions, classes, and scripts for test automation. PyTest + Allure — Experience writing structured test cases with fixtures, markers, and generating Allure evidence reports. VS Code + GitHub Copilot — Proficient in AI-assisted development workflows; knows how to review, refine, and validate Copilot suggestions

Prompt Engineering — Ability to craft effective prompts for code generation, test case creation, and QA analysis using LLMs (ChatGPT, Copilot, etc.). Agent Design & MCP Basics — 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 — t

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