QA Engineer with 2+ years in AI-driven Platforms and Automation Testing
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Results-driven and Detail-oriented Manual and Automation Tester with over 2.7 years of hands-on experience in Al-driven voice Platforms, Experienced in testing Agentic Al voice agents, SIP trunk-based calling systems, Evals and real-time conversation workflows. Skilled in validating Al model responses, Telephony Integrations, and End-to-End call flows to ensure high reliability of voice automation systems., Black Box, API, Functional Testing. Skilled in analyzing requirements, documenting test scenarios, and delivering clear, high-quality defect reports. Proficient in creating comprehensive test documentation and working with diverse datasets and evaluation metrics.
KIT
Bachelor of Technology · IT
January 1, 2017 – January 1, 2021
ZestGeek Solutions Private Limited
Software Tester
November 1, 2025 – Present
Mohali, Punjab, India
Infrablok India Private Limited
Quality Assurance Engineer
June 1, 2023 – August 1, 2025
Noida, Uttar Pradesh, India
Python Basic Certification
The Next Level Python
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's experience across two companies, including a current role focused on cutting-edge AI voice platforms, demonstrates adaptability and a willingness to engage with diverse and evolving technologies. Their involvement in ML training data generation and prompt optimization suggests an interest in contributing beyond traditional QA boundaries, which aligns well with innovative and fast-paced environments. The breadth of testing skills and tools used indicates a versatile and proactive approach to quality assurance.
Soft Skills & Operational Fit
The candidate demonstrates strong operational fit through their detailed descriptions of participating in Scrum calls, collaborating with development and product teams, and managing defect lifecycles. Their experience in documenting test scenarios, creating test cases, and generating reports indicates good organizational and communication skills within an Agile environment. The ability to work with cross-functional teams for UAT and ML data generation also highlights collaborative soft skills.