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Full Stack Engineer with 3+ years in Spring Boot, React.js, and AI/ML Systems
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Junior Full Stack Developer with 1+ year of experience building scalable backend systems and ERP modules using Spring Boot, React.js, SQL Server and exposure to .NET-based systems. Strong in designing and implementing REST APIs, modular architectures and asynchronous workflows using RabbitMQ to improve system reliability and performance. Currently building an AI-powered Internal Knowledge Assistant using Retrieval-Augmented Generation (RAG) architecture with Spring AI, PostgreSQL (pgvector) and OpenAI embeddings, enabling semantic search and contextual information retrieval. Skilled in backend integration, debugging and building production-ready applications with a focus on clean code, performance optimization and scalable system design, with the ability to quickly learn new technologies and contribute effectively.
RUHM INNOVATION PVT LTD
Junior Full Stack Developer
December 1, 2024 – Present
India
Megdap Innovation Lab Pvt Ltd
Project Coordinator & Linguistic Data Specialist
December 1, 2022 – August 1, 2024
India
Centre for Artificial Intelligence and Robotics (CAIR), DRDO
Intern - Active Noise Cancellation Project
January 1, 2018 – March 1, 2018
India
AI-Powered Internal Knowledge Assistant (RAG-based System)
June 1, 2026 – Present
Designed and implemented a modular Retrieval-Augmented Generation (RAG) pipeline for querying internal engineering documents using semantic search. Built document ingestion pipeline including file upload, text extraction, and chunking, with embedding generation and vector storage integration using PostgreSQL (pgvector). Integrated OpenAI-based embeddings and pgvector for semantic search; validated pipeline execution up to embedding stage (external API dependent). Designed vector-based retrieval using cosine similarity and ivfflat indexing for efficient top-k search. Structured backend using Spring Boot and Spring AI with modular architecture separating document processing, ingestion, and vector storage components. Containerized PostgreSQL (pgvector) using Docker for consistent development and environment isolation. Designed end-to-end RAG architecture (ingestion → retrieval → generation) and planned scalable async processing using RabbitMQ and MinIO. Currently implementing retrieval layer (top-k similarity search) and chat module for full RAG system.
Material Management System (ERP Modules)
December 1, 2024 – June 1, 2026
Developed ERP-based modules with frontend-backend integration using React.js and .NET-based systems. Implemented RabbitMQ-based asynchronous email for notification module with SMTP fallback, improving reliability, performance, and service decoupling. Designed configuration-driven dynamic forms and backend-controlled UI behavior, reducing hardcoded logic and improving scalability.
Data Science Program
Career Redefine
March 1, 2025 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from ERP modules to an AI-powered RAG system, indicates adaptability and a willingness to explore new technologies. Their experience in both backend and frontend development, coupled with exposure to AI/ML, aligns well with the dynamic requirements of a Full Stack Engineer role. The previous role as a Linguistic Data Specialist, while not directly technical, shows an interest in data and AI, which could be a cultural asset in an innovation-driven environment. However, the relatively short professional experience (1+ year as Junior Full Stack Developer) suggests a need for continued mentorship and growth within a senior role.
Soft Skills & Operational Fit
The candidate demonstrates good collaboration skills through Agile development participation and leveraging AI-assisted tools for productivity. Their experience as a Project Coordinator also suggests organizational and coordination abilities. The focus on clean code, performance optimization, and scalable system design indicates a strong operational fit for a development team.