About
SDET with 2 years of experience building and scaling UI and API automation using Python, Pytest, and Selenium. Experienced in designing reliable test frameworks, reducing flaky test, and integrating automation into CI/CD pipelines for continuous delivery. Hands-on exposure to AI-driven systems, including validation of LLM-based diagnosis pipelines and anomaly detection models using RAG. Strong focus on improving system reliability, debugging complex failures, and ensuring production-grade quality across distributed systems.
Skills & Expertise (26)
Work Experience
SDET
Capgemini
May 2024 - Present
Designed and maintained UI & API automation test cases using Pytest, Selenium, and REST APIs, improving regression coverage for critical modules. Reduced test flakiness by 30% by refactoring selenium scripts with better synchronization and element handling techniques. Contributed to the development of an Agentic AI-based Auto-Heal system for anomaly detection, incident correlation, and automated diagnosis using multi-sensor data. Validated and compared SLM models (LLaMA 3.2, Phi-3) with RAG-based grounding for generating actionable diagnosis outputs. Ensured end-to end pipeline reliability, performance (SLOs), and consistency across CLI and UI-based workflows.
Education
Bachelor of Technology in Computer Science and Engineering - CMR Engineering College
- 2023 · Afghanistan
Certifications
AWS Cloud Practitioner
AWS · 2025
Python
Hacker-Rank · 2024
Smart Coder
Smart Interviews · 2022
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Visa Status
Citizen
Relocation
Open to Relocation
Skills (26)
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