Full Stack AI Engineer with less than a year in LLM integration & Generative AI workflows.
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Full-Stack Generative AI Engineer with industry experience in LLM integration, vector databases, agentic AI workflows, and enterprise backend development. Proficient in Python, Java (Spring Boot, Microservices, JPA/Hibernate), Flask, React, and SQL. Experienced with Anthropic Claude (Claude Code), OpenAI, LangChain, and RAG architectures. Track record of building intelligent, scalable, production-grade applications.
Dehradun Institute of Technology
B.Tech · Computer Science (Specialization in AI & ML)
August 1, 2021 – June 30, 2025
M Moser Associates
AI WORKFLOW DEVELOPER
August 1, 2025 – March 31, 2026
Mumbai, Maharashtra, India
AI-Driven Client Proposal & Presentation Generator
June 1, 2021 – July 31, 2025
Designed and built an end-to-end AI-powered proposal automation platform that generates tailored client proposals using structured data from MySQL. Leveraged OpenAI LLMs to dynamically manipulate and refine proposal narratives based on user-selected parameters and business context. Automated PowerPoint generation using the python-PPTX library, transforming AI-generated content into professionally structured presentations. Integrated SharePoint for document storage and retrieval, enabling automated upload and versioning of generated proposals. Implemented secure enterprise authentication using MSAL and Microsoft Graph APIs, ensuring role-based access and compliance. Developed a responsive React frontend and robust Flask backend to orchestrate AI workflows and user interactions.
AI-Powered Image Similarity Search
June 1, 2021 – July 31, 2025
Developed an AI-driven image similarity search system by generating vector embeddings and indexing SharePoint-hosted images using pg vector. Implemented semantic vector search to retrieve visually and contextually similar images, enabling fast and accurate discovery across large SharePoint repositories. Integrated Microsoft Graph API to securely fetch and manage SharePoint assets, ensuring seamless enterprise data access. Built scalable backend services in Python and Flask and an intuitive React-based frontend for efficient search and visualization workflows. Optimized embedding generation and similarity queries for performance and reliability in production environments.
View ProjectVirtual Try-On
June 1, 2021 – July 31, 2025
Built a virtual clothing try-on application using the pretrained VITON-HD model, a GAN-based framework for high-resolution image synthesis. Leveraged geometric warping and attention mechanisms to align garments with user poses and synthesize photorealistic try-on results. Designed preprocessing workflows for user uploads (pose estimation, segmentation) and post-processing for artifact reduction. Integrated PyTorch-based inference pipelines into a scalable web backend built using Flask.
View ProjectAI Movie Recommendation System
June 1, 2021 – July 31, 2025
Built an intelligent movie recommendation system using semantic search with all-mpnet-base-v2 embeddings to match user preferences with a database of 9,672+ movies. Implemented vector similarity search using cosine similarity algorithms to provide highly accurate movie recommendations based on natural language descriptions. Integrated Supabase as the vector database for efficient storage and retrieval of movie embeddings with custom PostgreSQL functions for similarity matching. Deployed interactive web interface using Gradio on Hugging Face Spaces, enabling users to get personalized movie recommendations through natural language queries.
View ProjectThe AI Engineer Path
Scrimba
June 1, 2026 – Present
Open-source AI Models
Scrimba
June 1, 2026 – Present
Learn RAG
Scrimba
June 1, 2026 – Present
Intro to Claude AI
Scrimba
June 1, 2026 – Present
AI for Everyone
Coursera
June 1, 2026 – Present
Machine Learning Classification
Coursera
June 1, 2026 – Present
Engineer AI Agents with Agent Development Kit (ADK)
June 1, 2026 – Present
Understand Google Cloud Agents
June 1, 2026 – Present
Build Agents with Agent Development Kit (ADK)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and a short-term professional experience demonstrate a strong interest and practical application in the AI/ML domain, aligning well with a 'Full Stack AI Engineer' role. The diversity of projects (proposal generation, image search, virtual try-on, movie recommendations) showcases a broad skill set and adaptability. The certifications further reinforce a proactive learning attitude, which is a positive indicator for cultural fit in a dynamic tech environment. However, the limited professional experience (less than a year) means the breadth of real-world collaboration and problem-solving in a team setting is yet to be fully demonstrated.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a structured approach to problem-solving and an ability to translate complex AI concepts into functional applications. The experience in building end-to-end systems suggests good operational fit for roles requiring full-stack development with an AI focus. However, without direct assessment data on communication, logical reasoning, or teamwork, it's difficult to fully evaluate soft skills and operational fit beyond technical execution.