Muskan Singhai profile photo 1 on Tal

Muskan Singhai

QA Engineer - AgenticAI |BBT| Automation Testing(Selenium)|Javascript| playwright| Jmeter |Jenkins|Java|Azure Devops| smoke|SDLC| STLC|Regression|UI/UX |RestAssured|Web&Mobile testing|POSTMAN|Cross browser testing|Appium

Pune District

1+ year of work experience

CS TECH Ai
- NowPresent

Executed end-to-end testing across release cycles including smoke, regression, functional, performance, and load testing. Automated 50+ test cases using Selenium WebDriver, reducing regression time by 30%. Built and maintained a Maven–TestNG automation framework. Designed and implemented REST API automation scripts and a BDD framework using Rest Assured, achieving 83% reduction in manual testing effort. Scheduled automated test runs using Jenkins, analysed failures, and generated detailed reports. Prepared test cases, managed test data, logged defects, and performed root cause analysis.
CS TECH Ai
- NowPresent

Executed end-to-end testing across release cycles including smoke, regression, functional, performance, and load testing. Automated 60+ test cases within 2 sprints using Selenium WebDriver, reducing regression time by 30%. Built and maintained a Maven–TestNG automation framework. Designed and implemented REST API automation scripts and a BDD framework using Rest Assured, achieving 83% reduction in manual testing effort. Scheduled automated test runs using Jenkins, analysed failures, and generated detailed reports. Prepared test cases, managed test data, logged defects, and performed root cause analysis.
CS TECH Ai
May 20261 moPresent

Pune District

🏠 AI HOUSE PLANNER PRO Multi-Agent AI-Based Smart House Planning System 📌 1. Introduction The AI House Planner Pro is an intelligent system that automates house planning using a multi-agent AI architecture. It integrates CrewAI, LLMs (LLaMA 3 via Ollama), Streamlit UI, and image/PDF generation tools to simulate a real-world architecture workflow. This system allows users to input housing requirements and instantly receive: • Layout planning • Interior design ideas • Cost estimation • Visual floor plan • Downloadable report 🎯 2. Objectives • Automate house planning using AI • Simulate collaboration between domain experts • Provide quick and structured house design solutions • Reduce dependency on manual architectural consultation • Deliver ready-to-use reports and visual outputs 🧠 3. System Architecture 🔹 Core Components 1. Frontend • Streamlit UI • Handles user inputs and displays outputs 2. AI Layer • CrewAI Framework • Multiple specialized AI agents 3. LLM Backend • Ollama (LLaMA 3 model) • Performs reasoning and content generation 4. Utility Modules • Floor plan generator (PIL) • PDF generator (ReportLab) 🔄 Workflow Diagram (Explain in PPT) 👉 Input → Task Creation → Multi-Agent Execution → Output Generation → Visualization + Download 🤖 4. Multi-Agent Design The system uses five specialized agents, each performing a specific task: ✅ 1. Requirement Analyzer • Extracts structured data from user input • Identifies: ◦ Plot size ◦ Rooms ◦ Budget ◦ Design style ✅ 2. Architect Agent • Designs the house layout • Determines: ◦ Room arrangement ◦ Space utilization ◦ Functional planning ✅ 3. Interior Designer Agent • Suggests: ◦ Furniture placement ◦ Color schemes ◦ Design themes ✅ 4. Cost Estimator Agent • Estimates construction cost • Provides: ◦ Budget range ◦ Cost breakdown ✅ 5. Report Generator Agent • Compiles all outputs • Produces structured final report
CS TECH Ai
Oct 20258 mosPresent

Baner, Pune, Maharashtra

NetCom Learning
Jan 20254 mosApr 2025

Remote

- Attended KT sessions on web and mobile applications to understand module flows. • Identified and reported defects using the project management tool. • Prepared test scenarios and test cases; executed tests accordingly. • Provided daily task updates, participated in stand-up meetings, and filled monthly timesheets.

Education

QSpiders - Software Testing Training Institute

Bachelor of Engineering - BE, Electronics and telecommunication

QSpiders - Software Testing Training Institute

20241 yr2025
Sipna College of Engineering & Technology, Amravati

Bachelor of Engineering, Electronics

Sipna College of Engineering & Technology, Amravati

20184 yrs2022

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Headline

QA Engineer - AgenticAI |BBT| Automation Testing(Selenium)|Javascript| playwright| Jmeter |Jenkins|Java|Azure Devops| smoke|SDLC| STLC|Regression|UI/UX |RestAssured|Web&Mobile testing|POSTMAN|Cross browser testing|Appium

About

SQL |Java | Manual Testing | SDLC| BBT |STLC| Automation testing | Frameworks & Tools |Selenium| DDT | Jira |TestNG |MAVEN| API Testing| Postman Tool | SDET

Location

Pune District

Work experience

Quality Assurance Intern at CS TECH Ai, Executed end-to-end testing across release cycles including smoke, regression, functional, performance, and load testing. Automated 50+ test cases using Selenium WebDriver, reducing regression time by 30%. Built and maintained a Maven–TestNG automation framework. Designed and implemented REST API automation scripts and a BDD framework using Rest Assured, achieving 83% reduction in manual testing effort. Scheduled automated test runs using Jenkins, analysed failures, and generated detailed reports. Prepared test cases, managed test data, logged defects, and performed root cause analysis.

Quality Assurance Engineer at CS TECH Ai, Executed end-to-end testing across release cycles including smoke, regression, functional, performance, and load testing. Automated 60+ test cases within 2 sprints using Selenium WebDriver, reducing regression time by 30%. Built and maintained a Maven–TestNG automation framework. Designed and implemented REST API automation scripts and a BDD framework using Rest Assured, achieving 83% reduction in manual testing effort. Scheduled automated test runs using Jenkins, analysed failures, and generated detailed reports. Prepared test cases, managed test data, logged defects, and performed root cause analysis.

Agentic AI Engineer at CS TECH Ai, May 2026 - Present · 1 mo, Pune District, 🏠 AI HOUSE PLANNER PRO Multi-Agent AI-Based Smart House Planning System 📌 1. Introduction The AI House Planner Pro is an intelligent system that automates house planning using a multi-agent AI architecture. It integrates CrewAI, LLMs (LLaMA 3 via Ollama), Streamlit UI, and image/PDF generation tools to simulate a real-world architecture workflow. This system allows users to input housing requirements and instantly receive: • Layout planning • Interior design ideas • Cost estimation • Visual floor plan • Downloadable report 🎯 2. Objectives • Automate house planning using AI • Simulate collaboration between domain experts • Provide quick and structured house design solutions • Reduce dependency on manual architectural consultation • Deliver ready-to-use reports and visual outputs 🧠 3. System Architecture 🔹 Core Components 1. Frontend • Streamlit UI • Handles user inputs and displays outputs 2. AI Layer • CrewAI Framework • Multiple specialized AI agents 3. LLM Backend • Ollama (LLaMA 3 model) • Performs reasoning and content generation 4. Utility Modules • Floor plan generator (PIL) • PDF generator (ReportLab) 🔄 Workflow Diagram (Explain in PPT) 👉 Input → Task Creation → Multi-Agent Execution → Output Generation → Visualization + Download 🤖 4. Multi-Agent Design The system uses five specialized agents, each performing a specific task: ✅ 1. Requirement Analyzer • Extracts structured data from user input • Identifies: ◦ Plot size ◦ Rooms ◦ Budget ◦ Design style ✅ 2. Architect Agent • Designs the house layout • Determines: ◦ Room arrangement ◦ Space utilization ◦ Functional planning ✅ 3. Interior Designer Agent • Suggests: ◦ Furniture placement ◦ Color schemes ◦ Design themes ✅ 4. Cost Estimator Agent • Estimates construction cost • Provides: ◦ Budget range ◦ Cost breakdown ✅ 5. Report Generator Agent • Compiles all outputs • Produces structured final report

QA Intern at CS TECH Ai, Oct 2025 - Present · 8 mos, Baner, Pune, Maharashtra

Quality Assurance Intern at NetCom Learning, Jan 2025 - Apr 2025 · 4 mos, Remote, - Attended KT sessions on web and mobile applications to understand module flows. • Identified and reported defects using the project management tool. • Prepared test scenarios and test cases; executed tests accordingly. • Provided daily task updates, participated in stand-up meetings, and filled monthly timesheets.

Education

Bachelor of Engineering - BE, Electronics and telecommunication, QSpiders - Software Testing Training Institute

Bachelor of Engineering, Electronics, Sipna College of Engineering & Technology, Amravati