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AI Engineer with 2+ years in AI, Machine Learning & Microservices
Full Stack Developer with 2.3 years of experience building scalable, high-performance web applications using React, TypeScript, Python, Java, and Microservices Architecture. Hands-on expertise in developing RESTful APIs, dynamic UI components, and real-time data-driven systems with PostgreSQL and Redis caching. Experienced in designing AI-powered solutions leveraging Large Language Models (LLMs), AI Agents, and NLP for intelligent data processing and automated insights. Strong background in Machine Learning, Deep Learning, and Computer Vision using TensorFlow, Keras, and OpenCV for image classification systems. Proficient in Docker, Kubernetes, CI/CD Pipelines, and cloud-based deployments. Skilled in data visualization, performance optimization, and system monitoring using Kibana. Adept at Agile Methodologies, problem-solving, and delivering user-centric, scalable solutions.
Banasthali Vidyapith
B.Tech · CSE
August 1, 2020 – June 30, 2024
UBS BUSINESS SOLUTIONS
SOFTWARE ENGINEER
August 1, 2024 – Present
India
SHAPEMYSKILLS PVT. LTD
SOFTWARE ENGINEER INTERN
May 1, 2023 – November 30, 2023
India
Plant Identification System with Medicinal Insights
June 18, 2026 – Present
Developed a full-stack web application for plant identification using Deep Learning and Computer Vision techniques. The system allows users to upload images, which are processed using OpenCV and passed through a trained CNN model (VGG16) for accurate classification. Built backend services using Flask to handle image processing, model inference, and result generation. Integrated TensorFlow and Keras for model training and deployment. The application provides detailed insights including plant name, description, medicinal benefits, and side effects. Designed an interactive and responsive frontend using HTML, CSS, and JavaScript to ensure seamless user experience. Tech Stack: Python, Flask, TensorFlow, Keras, OpenCV, NumPy, CNN (VGG16), HTML, CSS, JavaScript, Image Processing, Git, GitHub.
AI-Powered Risk Management Platform
June 18, 2026 – Present
Developed an AI-powered risk management platform to analyze market and treasury data using Large Language Models (LLMs) and intelligent AI Agents. The system enables users to input natural language queries, which are processed to dynamically generate SQL queries for real-time data retrieval from PostgreSQL. Designed scalable Microservices Architecture with robust RESTful APIs to ensure seamless data flow and system integration. Implemented Redis caching to enhance performance and reduce latency. Integrated advanced data visualization features including trend graphs, tree-based structures, and analytical dashboards for better decision-making. Deployed using Docker and Kubernetes, with monitoring and logging via Kibana to ensure system reliability and observability. Tech Stack: React, TypeScript, Python, Java, Microservices, REST APIs, PostgreSQL, Redis, Docker, Kubernetes, LLMS, AI Agents, Data Visualization, Kibana, GitLab, CI/CD, JIRA, Nexus IQ.
Cultural Fit Analysis
The candidate's project diversity, ranging from an AI-powered risk management platform to a plant identification system, showcases adaptability and a broad interest in applying AI across different domains. The listed skills cover a wide spectrum of technologies, from frontend to backend, databases, DevOps, and core AI/ML, indicating a versatile and continuous learning mindset. The experience at UBS Business Solutions as a Software Engineer aligns well with a professional, enterprise-level development culture. The candidate's profile suggests a proactive and technically curious individual who can contribute to diverse technical challenges.
Soft Skills & Operational Fit
The candidate's resume highlights experience with Agile/Scrum methodologies, cross-functional team collaboration, and a focus on delivering user-centric solutions. This indicates a good operational fit for modern development environments. The emphasis on performance optimization, caching strategies, and system monitoring (Kibana) suggests a proactive approach to system reliability and efficiency. The detailed project descriptions and experience section demonstrate clear communication regarding technical contributions and responsibilities.