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AI Engineer with less than a year in ETL, Data Processing & Machine Learning
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Detail-oriented Software Engineer with experience in developing and maintaining ETL pipelines using PySpark and Python on Databricks. Skilled in SQL for data validation and analysis across large datasets. Proven ability in building multi-agent GenAI systems, implementing RAG with ChromaDB, and utilizing various AI/ML models for deepfake detection. Eager to apply strong technical and analytical skills to innovative engineering challenges.
Bharati Vidyapeeth's College of Engineering for Women, Pune
B.E. · Computer Engineering
August 1, 2021 – June 30, 2025
Capgemini
Software Engineer
October 1, 2025 – Present
Pune, Maharashtra, India
My Softwares
Software Development Intern
December 1, 2023 – February 1, 2024
Pune, Maharashtra, India
Financial Crime Investigation Copilot (GenAI / Multi-Agent)
June 1, 2026 – Present
• Building a multi-agent GenAI system for AML/KYC investigation using LangGraph for agent orchestration and LangChain for LLM pipeline construction. • Implemented Retrieval-Augmented Generation (RAG) with ChromaDB as the vector store to ground agents in financial crime compliance documents and transaction context. • Integrated Groq API (Llama 3.3 70B) for fast, low-latency inference; built an interactive investigation interface using Streamlit.
View ProjectSynthetic Media Detection using Hybrid Model (Deep Learning)
June 1, 2026 – Present
• Developed hybrid deepfake detection system achieving 94% accuracy using ResNeXt-50, Vision Transformer, and Optical Flow CNN. • Built interactive UI with Gradio for video uploads and result visualization.
View ProjectHybrid Approach for Video Deepfake Detection Using ResNeXt-50, ViT, and Optical Flow
IEEE
January 1, 2025 – Present
A Comparative Analysis of ResNeXt-LSTM and GAN for Deepfake Video Classification
IEEE
January 1, 2025 – Present
Diploma Course In German
SPPU, Pune
July 1, 2023 – Present
Certificate Course In German
SPPU, Pune
July 1, 2022 – Present
Cultural Fit Analysis
The candidate's project portfolio, particularly the GenAI and Deep Learning projects, aligns well with an AI Engineer role, showcasing a strong interest and practical application in the field. The diversity of technologies used (LangGraph, LangChain, RAG, PySpark, Deep Learning frameworks) indicates adaptability and a broad technical curiosity. The experience in ETL pipelines and SQL also suggests a pragmatic approach to data handling, which is crucial for real-world AI systems. The candidate's academic achievements and publications further reinforce a commitment to continuous learning and technical excellence.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative through personal projects and publications, indicating a proactive and self-driven approach. The project descriptions are clear and highlight technical contributions. While direct team collaboration experience in AI projects is not explicitly detailed, the nature of the projects suggests an ability to manage complex technical tasks. The candidate's academic background and early career experience at Capgemini suggest a structured approach to problem-solving.