AI Engineer with less than a year in LLM Applications & Data Science
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer with expertise in Generative AI and LLM Applications. Possesses strong skills in Python, SQL, and modern AI/ML frameworks like PyTorch and TensorFlow. Experienced in building and deploying AI solutions, including resume parsers, RAG systems, and analytics platforms, demonstrating proficiency in NLP, prompt engineering, and cloud technologies such as AWS and Kubernetes.
Navrachana University, Vadodara
B.Tech · Computer Science Engineering
August 1, 2022 – June 30, 2026
Digikentro
Generative AI Intern
January 1, 2026 – April 1, 2026
Vadodara, Gujarat, India
AI Hotel Booking Agent
June 1, 2026 – Present
Conversational multi-turn booking assistant using Flask and Google Gemini LLM with Google Calendar API integration and automated email notifications for reservation confirmations. Implemented human-in-the-loop approval workflows before finalizing bookings, ensuring reliability in agentic decision-making with clean dialogue management.
View ProjectMovie Booking Platform CI/CD & Kubernetes
June 1, 2026 – Present
Implemented CI/CD pipelines via GitHub Actions for automated Docker builds; deployed backend services on Kubernetes using Deployments, Services, ConfigMaps, and Secrets.
View ProjectAutonomous Data Analyst - LLM-Powered Analytics Platform
June 1, 2026 – Present
Converts natural language queries into SQL workflows and auto-generates insights, charts, forecasts, and reports – cutting manual analysis effort by ~90% in under 10 seconds. Implemented automatic visualization selection and trend detection using GROQ LLM reasoning pipelines with support for multi-step analytical workflows.
View ProjectRetrieval-Augmented Document Q&A System
June 1, 2026 – Present
Built end-to-end RAG pipeline with document ingestion, chunking, and FAISS vector embeddings enabling contextual search and Q&A across large document collections. Exposed context-aware question answering via REST APIs; optimized retrieval accuracy through structured chunking strategies and embedding evaluation.
View ProjectPharmaceutical Tablet Anomaly Detection - Computer Vision
June 1, 2026 – Present
Built YOLO-based inspection system with EasyOCR for batch/expiry extraction; explored Vision-Language Models for descriptive anomaly explanations to improve traceability.
View ProjectE-commerce Analytics & Cart Prediction
June 1, 2026 – Present
AWS Glue/Athena/S3 pipeline on multi-GB datasets; trained Random Forest model to predict cart additions from customer behavior with sales trend dashboards.
Natural Language Processing
AWS Academy
June 1, 2026 – Present
Data Engineering
AWS Academy
June 1, 2026 – Present
Cloud Foundations
AWS Academy
June 1, 2026 – Present
Machine Learning Foundations
AWS Academy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong interest and practical application in cutting-edge AI/ML technologies, particularly Generative AI and LLMs, which aligns well with an AI Engineer role. The diversity of personal projects (hotel booking, data analysis, document Q&A, anomaly detection, music lyric generation) indicates a proactive, self-driven individual eager to explore different domains within AI. The experience with various tools and frameworks (LangChain, FastAPI, Next.js, AWS services) suggests adaptability and a willingness to learn new technologies. The certifications in AWS Academy further reinforce a commitment to continuous learning and professional development, which are positive indicators for cultural fit in a dynamic tech environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting strong problem-solving and analytical skills. The implementation of human-in-the-loop workflows and evaluation of retrieval accuracy points to a detail-oriented approach. The scaling of the resume parser pipeline demonstrates an understanding of production-grade requirements and cost efficiency. However, without direct interview data, specific soft skills like teamwork, leadership, or direct communication style cannot be fully assessed.