Generative AI Engineer with less than a year in Python & LLM-powered applications
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Generative AI Engineer and Python Developer with an MCA and PG Diploma in Big Data Analytics (CDAC Mumbai). Skilled in building LLM-powered applications, RAG pipelines, and Prompt Engineering, with hands-on experience in LangChain, Vector Databases, Python, SQL, PySpark, Databricks, and AWS. Proven track record of developing AI-powered chatbots, intelligent recommendation systems, and scalable data pipelines – passionate about shaping the future of intelligent applications.
PG Diploma in Big Data Analytics (PGDBDA)
PG Diploma · Big Data Analytics
August 1, 2025 – June 30, 2026
SSBT College of Engineering and Technology, Jalgaon
Master of Computer Applications (MCA) · Computer Applications
August 1, 2022 – June 30, 2024
Moolji Jetha College, Jalgaon
Bachelor of Computer Science · Computer Science
August 1, 2019 – June 30, 2022
Paarsh Infotech
Python Development Intern
February 1, 2024 – May 1, 2024
Nashik, Maharashtra, India
Customer Churn Deep Statistical Analysis
June 1, 2026 – Present
Processed and analyzed large-scale structured customer data on Databricks using Python and advanced SQL, reducing data preparation time by ~40%. Applied hypothesis testing (t-test, chi-square), correlation analysis, and confidence intervals to identify key churn drivers with statistical significance. Built cohort and segmentation analysis using SQL window functions, CTEs, and aggregations to isolate high-risk customer segments. Designed interactive Power BI dashboards and Seaborn visualizations (KDE plots, box plots, trend charts) for stakeholder reporting.
TripSync - AI-Based Travel Planning System (GenAI)
June 1, 2026 – Present
Architected a RAG pipeline integrating LLMs with LangChain and Vector Databases for context-aware, personalized travel recommendations with real-time data retrieval. Engineered Prompt Engineering strategies to optimize LLM outputs for travel planning use cases, improving recommendation accuracy and response quality. Built a Python data processing engine using Pandas and NumPy to clean and analyze large unstructured travel datasets; implemented TF-IDF and K-Means clustering for intelligent place ranking. Exposed the AI pipeline via a FastAPI backend and deployed the end-to-end application on AWS, demonstrating cloud orchestration and automated AI workflows.
Recipe Management System
June 1, 2026 – Present
Built a full-stack web application with CRUD operations using OOP design patterns; designed normalized SQL schemas and optimized queries. Automated data validation and processing workflows with Python scripts; managed version control via Git following SDLC best practices.
AWS Academy Graduate Data Engineering
AWS Academy
June 1, 2026 – Present
AWS Academy Graduate - Cloud Foundations
AWS Academy
June 1, 2026 – Present
AWS Academy Generative AI Foundation
AWS Academy
June 1, 2026 – Present
Python (Core)
Info Planet, Jalgaon
June 1, 2026 – Present
PG-DBDA (Post Graduate Diploma in Big Data Analytics)
CDAC, Mumbai
February 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from GenAI-based travel planning to statistical churn analysis and full-stack recipe management, indicates a broad interest and willingness to tackle different technical challenges. The target role of 'Generative AI Engineer' aligns well with their 'TripSync' project and AWS Generative AI Foundation certification. The academic background in Big Data Analytics further supports a data-driven culture. However, the lack of team-based professional projects beyond an internship makes it difficult to fully assess collaboration and leadership in a senior context.
Soft Skills & Operational Fit
The candidate demonstrates a structured approach to project development, including SDLC best practices, Git-based version control, and code reviews. Their project descriptions highlight problem-solving (e.g., reducing data preparation time, optimizing LLM outputs) and a focus on delivering tangible results. The diverse project portfolio suggests adaptability and a proactive learning attitude. However, with limited professional experience, the depth of operational fit in a senior role is yet to be fully proven.