mcp-testrail-slack
AIComing SoonProduction MCP integration — automated test result publishing & Slack notifications.
I build intelligent, AI-augmented test automation systems that help engineering teams ship faster with confidence.
Years Experience
Companies
Spot Awards
Domains Shipped

Quality Engineering Lead
SDET · AI-Driven Test Architect · GenAI Specialist
About Me
Engineer, leader, and builder — the person behind the automation.

Quality Engineering Lead
Mahesh Wankhede
Professional
I build intelligent, AI-augmented test automation systems that help engineering teams ship faster with confidence.
I'm a Quality Engineering Lead who treats QA as systems engineering — not checkbox testing. Over 8 years, I've moved from writing Selenium suites to architecting AI-augmented automation: production MCP integrations, Playwright frameworks at scale, and GenAI workflows that cut manual effort across wagering, healthcare, and digital platforms. I research first, build POCs fast, and ship what actually works in production.
Based in
Pune, India
Remote
Open worldwide
Currently
SDET/QE Lead
Education
Master in CS · CGPA 9.1
currently building →
Recognition
Capabilities
Interactive capability map — hover any skill to see where I've used it in production.
Generative AI & LLMs
MCP (Model Context Protocol)
Prompt Engineering
GitHub Copilot & Cursor
RAG-based QA Tooling
Multi-agent Workflows
AI Innovation Layer
MCP Integrations
ProductionProduction TestRail → Slack pipeline. Natural-language API queries for live test data.
RAG QA Knowledge
POC → ProdContextual retrieval over internal docs — testers query knowledge bases conversationally.
GenAI Test Workflows
Active R&DAI-assisted test generation, GCP log analysis, and automated PR reviews in CI.
Open Source & R&D
Live repos on GitHub plus internal R&D work being open-sourced. Honest showcase — no filler.
Production MCP integration — automated test result publishing & Slack notifications.
Scalable E2E automation for high-traffic wagering — API + UI with dynamic data loader.
Practice automation target — HTML grocery list app for test exercises.
TodoMVC test automation sandbox for framework experimentation.
Utility web app for generating rent receipts.
RAG-based tool for contextual QA documentation retrieval.
LLM-powered test scenario & edge case generation utility.
Career
Every role tells a story of increasing scope — from writing tests to architecting AI-augmented quality systems.
Received recommendations from colleagues and clients — sourced from my LinkedIn profile.
“I've had the pleasure of collaborating with Mahesh at Publicis Sapient, where he serves as a QA Automation Engineer. Mahesh's expertise in automation testing is truly impressive, and his contributions have significantly enhanced the quality and efficiency of our software development process. He possesses a keen analytical mind and a meticulous attention to detail, which enables him to identify and rectify even the most intricate bugs and issues. Mahesh's dedication to ensuring product excellence is evident in his thorough approach to testing and his proactive attitude towards problem-solving. Moreover, Mahesh is an excellent team player, always willing to share his knowledge and support his colleagues to achieve collective success. I highly recommend Mahesh for his outstanding skills, professionalism, and unwavering commitment to delivering top-notch results.”
Java Developer | Senior Software Developer · Airtel Digital
Worked with Mahesh on the same team
LinkedIn Recommendations
Recommendations on LinkedIn from people who've worked with me — managers, peers, and clients.
Writing
Thoughts on AI, QA automation, and staying relevant — published on Medium.
The rise of Generative AI has transformed the IT industry, sparking both excitement and fear among developers, testers, and tech professionals.
Am I falling behind? A honest look at how QA engineers can stay relevant as AI reshapes testing.
Which AI tool is right for your workflow? A practical comparison for engineering teams.
Exploring the future of autonomous AI in software testing — promise, pitfalls, and pragmatism.