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AI Engineer with less than a year in cloud-native event streaming and Generative AI.
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Assessing your cultural and operational fit
Highly motivated AI/ML Engineer with experience in cloud-native event streaming and Generative Al, seeking to design, develop, and deploy Generative Al applications. Proficient in Python and skilled in building LLM-powered applications using various frameworks, with a strong understanding of RAG pipelines and vector databases.
Institute of Aeronautical Engineering
B.E. · Electronics & Communication Engineering
August 1, 2020 – June 30, 2024
Wipro Limited
Project Engineer
June 1, 2025 – April 1, 2026
India
Customer Churn Prediction Using Deep Learning
June 24, 2026 – Present
Developed a telecom churn prediction solution, applying preprocessing, feature engineering, and model optimization to identify high-risk customers with 90% (est.) accuracy.
Image Based Vehicle Detection
June 24, 2026 – Present
Developed a vehicle detection, classification, and counting system using computer vision techniques for video analytics, achieving 95% (est.) detection accuracy.
Introduction to Cyber Security
Cisco
June 1, 2026 – Present
Web Development Certification
CodeClause
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate initiative in AI/ML domains. Their professional experience at Wipro Limited, a large IT services company, suggests an ability to work in structured environments. The stated interest in cloud-native event streaming and Generative AI aligns well with modern AI engineering roles. However, the overall breadth of experience is limited to a single professional role and two academic projects, which might indicate a narrower exposure to diverse team dynamics or project types.
Soft Skills & Operational Fit
The candidate's experience in developing technical documentation, architecture diagrams, and migration reports suggests good communication and organizational skills. Their work on monitoring dashboards and auto-scaling indicates an understanding of operational efficiency and system observability. The project descriptions are clear and quantify achievements, which is a positive indicator for communication.