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Senior AI Engineer with 5+ years in AI/ML & Data Analysis
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AI/ML Engineer and Data Analytics enthusiast with 5+ years of experience in software quality assurance. Currently transitioning into AI Engineering and Data Engineering roles with hands-on knowledge of Python, Generative AI, Retrieval-Augmented Generation (RAG), AI agents, and data analysis using Pandas and Power BI. Strong analytical background developed through QA testing, defect analysis, and system validation. Interested in building AI-powered applications, intelligent automation systems, and scalable data pipelines.
Bharati Vidyapeeth University College of Engineering
Bachelor of Engineering · Computer Science
August 1, 2016 – June 30, 2019
Ubisoft India Studios
Senior QA Tester
March 1, 2024 – Present
Pune, Maharashtra, India
Ubisoft India Studios
QA Tester
March 1, 2022 – July 1, 2024
Pune, Maharashtra, India
Ubisoft India Studios
Junior QA Tester
March 1, 2021 – March 1, 2022
Pune, Maharashtra, India
AI Workflow Automation
June 1, 2026 – Present
Created AI-driven workflows using Zapier and LLM tools to automate repetitive tasks and knowledge retrieval.
AI Knowledge Assistant (RAG)
June 1, 2026 – Present
Built a Retrieval-Augmented Generation system using Python and vector databases for document-based question answering.
Data Analysis with Python
June 1, 2026 – Present
Performed exploratory data analysis using Pandas to identify trends and insights.
Generative AI Certification
Be10x
January 1, 2026 – Present
Python Using AI
Be10x
January 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, while focused on AI, is currently limited to personal projects. The professional experience is entirely within QA, which is a different domain from AI Platform Engineering. While the candidate is actively upskilling, the direct alignment with a senior AI Platform Engineer role is not yet fully established through professional experience. The certifications are future-dated, which means they are not yet completed.
Soft Skills & Operational Fit
The candidate's extensive QA background suggests strong attention to detail, systematic problem-solving, and collaboration within Agile environments. These are valuable for an AI Platform Engineer role, particularly in ensuring the reliability and quality of AI systems. The transition from QA to AI engineering indicates adaptability and a proactive learning attitude.