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AI Engineer with 1+ years in LLMs, Agentic AI, and Machine Learning with 1.0 years of experience.
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AI Engineer specializing in Large Language Models (LLMs), Agentic AI Systems, Multi-Agent Workflows, Retrieval-Augmented Generation (RAG), and Machine Learning. Experienced in designing AI agents, semantic retrieval systems, enterprise AI automation solutions, and production-grade ML pipelines using Python, PyTorch, FAISS, and modern AI frameworks.
Delhi Technological University
M.Tech · Computer Science Engineering
August 1, 2024 – June 30, 2026
Sinhgad College of Engineering, Pune
B.E. · Computer Science Engineering
August 1, 2018 – June 30, 2022
Sinhgad College of Engineering, Pune
Honours · Artificial Intelligence and Machine Learning
August 1, 2018 – June 30, 2022
STMicroelectronics
AI Project Trainee
July 1, 2025 – June 1, 2026
Noida, Uttar Pradesh, India
Voice Finance Buddy | Multi-Agent Financial AI Assistant
June 1, 2026 – Present
• Architected a multi-agent financial assistant using GPT-4, Whisper, Retrieval-Augmented Generation (RAG), and persistent memory for multilingual (Hindi/English/Hinglish) interactions. • Designed intent-based routing and function-calling workflows across Budget, Expense, Investment, and Tax specialist agents. • Implemented conversation memory, financial knowledge retrieval, and guardrail mechanisms for context-aware and secure responses. • Developed an end-to-end voice AI pipeline (Speech-to-Text → Agent Reasoning → Tool Execution → Text-to-Speech) achieving sub-3 second response latency.
View ProjectLocal RAG System | Enterprise Document Intelligence
June 1, 2026 – Present
• Built an end-to-end Retrieval-Augmented Generation (RAG) system using FAISS, Sentence Transformers, and local LLMs for technical document question answering. • Implemented semantic chunking, vector indexing, query expansion, and similarity-based retrieval pipelines across large technical document collections. • Developed context-aware prompting and grounded answer generation to reduce hallucinations and improve response quality. • Designed a fully local inference architecture enabling secure document intelligence without reliance on external APIs.
View ProjectAI-Powered Inventory & Demand Forecasting System
June 1, 2026 – Present
• Developed a demand forecasting platform using Prophet, Pandas, and NumPy for inventory planning and future demand prediction. • Implemented inventory optimization algorithms including Economic Order Quantity (EOQ) and Reorder Point (ROP) calculations for supply-chain decision support. • Built automated forecasting pipelines incorporating feature engineering, preprocessing, and real-time prediction workflows. • Developed an interactive Streamlit dashboard for inventory monitoring, forecasting visualization, and operational analytics.
View ProjectRoad Pothole Detection System
June 1, 2026 – Present
• Developed a real-time road defect detection system using YOLOv4 for automated pothole identification from images and video streams. • Built data preprocessing, model training, and inference pipelines achieving high-accuracy object detection performance. • Optimized inference workflows for low-latency processing and deployment-ready computer vision applications. • Developed monitoring and visualization components for rapid road-condition assessment and infrastructure inspection.
View ProjectEmotion-Aware Music Recommendation System
June 1, 2026 – Present
• Developed a CNN-based facial emotion recognition model for real-time affect detection from webcam inputs. • Built an emotion-driven recommendation engine that maps user sentiment to personalized music playlists. • Implemented image preprocessing, feature extraction, and deep learning workflows achieving 90%+ emotion classification accuracy. • Integrated computer vision and recommendation pipelines to deliver an adaptive and personalized user experience.
View ProjectMicrosoft Azure AI Essentials Professional Certificate
Microsoft
June 1, 2026 – Present
Career Essentials in Generative AI by Microsoft and LinkedIn
Microsoft & LinkedIn
June 1, 2026 – Present
Career Essentials in GitHub Professional Certificate
GitHub
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse range of personal projects, covering areas like computer vision, recommendation systems, RAG, demand forecasting, and multi-agent financial assistants, indicates a strong curiosity and passion for AI. This aligns well with an innovative and research-driven culture. The focus on building fully local inference architectures and optimizing for real-world deployment suggests a pragmatic and resourceful mindset. The candidate's academic pursuits and certifications also demonstrate a commitment to continuous learning and professional development, which is a strong cultural fit for growth-oriented teams.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a strong ability to take initiative and drive projects from conception to deployment. The focus on end-to-end solutions and optimization suggests a practical, results-oriented approach. The multi-agent and RAG projects highlight problem-solving skills and an understanding of complex system design. The internship experience at STMicroelectronics further reinforces an ability to work in an industrial setting and contribute to enterprise-level AI solutions.