Anees Mufti

Software Quality Assurance Engineer

The standard is non-negotiable excellence, and I guarantee it through automation.

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About my work

I am a Software Quality Assurance Engineer focused on Test Architecture and automation efficiency. With over 3 years of experience (7 including freelancing since 2019), I specialize in designing and deploying end-to-end frameworks (Selenium/C#) to achieve non-negotiable quality. My work consistently reduces manual effort, accelerates releases, and ensures robust functionality for high-impact applications, contributing to 100% test success rates for major clients.

Core Expertise & Technologies

  • Testing Types: Functional, Regression, E2E, Performance, API, AI Feature Validation
  • Automation Frameworks: Selenium, Postman, Rest Assured
  • Languages: C#, Python, JavaScript, Java
  • Methodologies: Agile, CI/CD Integration (GitLab/GitHub Actions)

Professional Experience

Professional Freelancer

Upwork | January 2019 - Present (7 years)

  • Skilled in software quality assurance, test automation, and validation of web and enterprise applications.
  • Experienced in designing and executing detailed test strategies, developing automated frameworks with Selenium and C#, and implementing testing within Agile and CI/CD environments.
  • Proficient in functional, regression, and performance testing, with a strong focus on maintaining product reliability and efficiency.
  • Additionally, adept in UX/UI design principles, applying user-centered insights to improve usability testing and enhance overall product quality.

Software Test Engineer

Geeks Ltd | December 2024 - November 2025 (1 year)

  • Led E2E quality assurance for AI-driven and enterprise applications, ensuring system reliability and optimal AI model performance.
  • Architected and maintained automated test frameworks using Selenium and C#, integrating them into continuous integration and agile release pipelines.
  • Developed and executed 2,730 manual and automated test cases, achieving an overall pass rate above 80%, with three major projects reaching a 100% test success rate.
  • Logged 1,365 detailed defect reports with supporting artifacts (screenshots/recordings), which significantly enhanced bug visibility and reduced issue resolution time.
  • Supported high-impact solutions for globally recognized clients (e.g., BBC, Dyson, UK Houses of Parliament), reinforcing the company's reputation for AI-enabled innovation.

Quality Assurance Automation Engineer

ProgNeo | March 2024 - December 2024 (10 months)

  • Performed QA and automation engineering across a diverse application portfolio.
  • Tested and verified various app categories, including e-commerce, legal/lawyer, mobile (makeup), and auditing applications.
  • Executed functional and regression testing for both web and mobile platforms.
  • Designed and implemented automated test scripts to accelerate quality validation.
  • Contributed to multi-platform stability by identifying key defects across specialized client software.

Quality Assurance Automation Engineer (Team Lead)

Center for Advanced Research in Engineering (CARE) | December 2022 - March 2024 (1 year 4 months)

  • Directed QA team and implemented comprehensive testing strategies for a major Enterprise Resource Planning (ERP) system, managing all manual and automated testing cycles.
  • Accelerated quality delivery by serving as the solo Automation Engineer for three months, automating a significant portion of the ERP application to streamline release pipelines.
  • Spearheaded defect resolution across critical modules (HRM, Finance, Inventory, etc.), overseeing the management and closure of 1,700+ bug reports to drive product quality.
  • Contributed key expertise to the entire product lifecycle, leveraging automation and early defect identification to ensure system stability and optimize the user experience.

UX/UI Designer (Part-time)

Future Vision DevSol | Sep 2022 - Nov 2022 (3 months)

  • Served as the sole UX/UI Designer, owning and executing the end-to-end design process at Future Vision Devsol.
  • Delivered comprehensive design solutions, including crafting highly intuitive user interfaces (UI) and developing visually compelling graphics.
  • Established and maintained the company's overall design strategy, ensuring a seamless, high-quality user experience (UX) across all digital platforms.

Research Scholar & Graphic Designer

National University of Sciences and Technology (NUST) | Dec 2021 - Feb 2022 (3 months)

Graphic Designer (Full-time)

  • Demonstrated exceptional graphic design skills while working as a Graphics Designer for the armed forces.
  • Successfully delivered high-quality visual materials, including videos, presentations, posters, and images, that effectively communicated key messages to the target audience.
  • Contributed to the Army's visual identity and ensured compliance with branding standards.

Research Scholar

  • Successfully served as a research scholar, contributing to cutting-edge research projects. Proficient in conducting in-depth research, writing scholarly papers, and creating compelling visuals.
  • Utilized LaTeX to efficiently prepare and format academic documents.
  • Demonstrated strong analytical skills and attention to detail, ensuring the accuracy and quality of research outputs.

My Impact & Metrics

Quantifying my commitment to speed, quality, and results.

3+ Years

Professional Experience

30+ Projects

Delivered & Launched

2,500+ Bugs

Defects Resolved

Code Quality & Contribution

95%
  • Code Coverage: 95%
  • Pull Requests Merged: 320

Delivery & Client Focus

4.8/5
  • Client Satisfaction: 4.8/5.0
  • Performance Boost: 30%

Automation Coverage by Type

E2E (Selenium)
93%
Test case Reusability
90%
Flakiness Reduction
85%

Focus on high-value, stable E2E and 100% API coverage.

Publications

A review of neuro-symbolic AI integrating reasoning and learning for advanced cognitive systems

This systematic review focuses on Neuro-Symbolic AI (NeSy), integrating deep learning with symbolic reasoning to enhance system interpretability and logical deduction. It evaluates NeSy frameworks for complex cognitive tasks, providing a roadmap for developing trustworthy and scalable AI.

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Adversarial and self-adaptive domain decomposition physics-informed neural networks for high-order differential equations

This research introduces an advanced PINN framework using adversarial learning and self-adaptive domain decomposition. It effectively addresses discontinuities and high-order differential equations, significantly improving computational accuracy and stability in complex engineering simulations.

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Education

National University of Sciences and Technology (NUST)

Master's degree, Computer Software Engineering

October 2019 – September 2022

Focused on advanced software design, quality assurance, and automated testing methodologies.

HITEC University Taxila

Bachelor of Science - BS, Computer Science

September 2015 – July 2019

Comprehensive study in algorithms, data structures, and fundamental programming concepts.

Contact Me

I am currently available for new projects and collaborations. Let's connect and discuss your next challenge.

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Made with ❤️ by Anees Mufti.

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