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Full Stack AI Engineer | RAG • Multi-Agent Systems • AI Workflow Automation | Java • Spring Boot • Fast API
I build production-ready software systems that combine strong backend architecture, modern full-stack development, and AI-powered automation to solve real-world problems at scale. My focus is on AI Product Engineering, Full Stack AI Development, and Enterprise-Grade Backend Systems — building applications that are secure, scalable, intelligent, and deployable in real production environments. I enjoy working at the intersection of backend architecture, AI workflows, automation systems, and user-focused product design. With a strong foundation in Java, Spring Boot, FastAPI, React, and modern system design, I like building solutions that handle concurrency, maintain data integrity, and deliver fast, reliable user experiences. I’m especially interested in AI-native products, intelligent automation, RAG systems, agentic workflows, and scalable products that can support real business use cases. My core interests and strengths include: • AI Product Engineering • Agentic AI & AI Workflow Automation • Full Stack Development • Backend Architecture & System Design • LLM Integration & AI-Native Features • Scalable Transaction Systems • Real-Time Applications • Production-Ready Engineering Technical stack: • Backend: Java, Spring Boot, FastAPI, REST APIs, Hibernate/JPA • Frontend: React.js, Next.js, Tailwind CSS, JavaScript • Databases: MySQL, MongoDB, PostgreSQL • AI & Automation: LLMs, AI architecture, automated workflows, intelligent job-matching systems • Systems & Tools: Docker, Git, Redis, Kafka, CI/CD basics Some of the projects I’ve built include: • UPI Lite Payment Engine — a high-concurrency financial transaction system designed with strict ACID compliance, atomic operations, and race-condition prevention to ensure secure and reliable money transfer logic. • RideFlow Management System — a scalable ride-sh
KL University
Master of Computer Applications, Artificial Intelligence & Machine Learning
June 1, 2026 – August 1, 2028
Rent Eco
Full Stack AI Engineer
May 1, 2026 – Present
luknow · Remote
Coding Age
Full Stack AI Engineer
February 1, 2026 – Present
Patna, Bihar, India · On-site
Coding Age
Aspiring Developer
January 1, 2025 – January 1, 2026
Patna, Bihar, India · On-site
BiharRozgar : Full-Stack AI Job Matchmaker & Agentic Automation Platform
March 1, 2026 – Present
Designed, architected, and developed an end-to-end AI-powered job portal to digitize a highly fragmented regional job market, bridging the gap between local talent and employers. Built with a modern micro-architecture mindset, this platform leverages autonomous AI workflows to eliminate manual hiring processes. 🚀 Key Engineering Highlights & Automation: Agentic AI Job Matchmaker: Engineered an autonomous background automation pipeline using FastAPI BackgroundTasks. The system dynamically fetches real-time database records and uses LLMs to analyze candidate skills against active job postings, generating automated match scores and contextual reasoning without human intervention. LLM Orchestration & Custom Chatbot: Built "Rozgar Mitra," a highly customized AI assistant integrated via the OpenRouter API. Applied advanced prompt engineering to automate candidate onboarding, career counseling, and user query resolution. High-Concurrency Backend Architecture: Developed a robust, asynchronous API layer using Python (FastAPI) and PostgreSQL (asyncpg), handling custom OTP delivery, JWT-based security, and complex relational data queries at scale. Premium Frontend Engineering: Built a highly responsive, high-conversion frontend using Next.js 14, TypeScript, Tailwind CSS, and Framer Motion, delivering a modern SaaS-level user experience. ⚙️ Tech Stack & Keywords: Python, FastAPI, Next.js 14, PostgreSQL, Agentic AI, LLM Orchestration, Workflow Automation, RAG Architecture, Asynchronous APIs, Docker, System Design.
Upi Lite Payment Engine
January 1, 2026 – Present
A high-performance, event-driven payment system built with Spring Boot 4.0.2, Java 21 (Virtual Threads), Kafka, and PostgreSQL. Implementing the Saga Pattern for distributed transactions and data consistency
Rideflow AI Backend
January 1, 2026 – April 1, 2026
A scalable, distributed ride-sharing platform backend built with Spring Boot Features include real-time location tracking (PostGIS), event-driven communication (Kafka), distributed locking (Redis), and AI-powered dynamic pricing
Blooms Blog Management System
January 1, 2026 – March 1, 2026
Blooms Blog Management System: A Core Java project evolving into an API‑driven platform. Features include blog creation, categories, user roles, comments, and search. Built with OOP, JDBC, and later REST APIs for CRUD, JSON responses, and authentication.
Full Stack Development
Coding Age
June 23, 2026 – Present
Introduction to Java Spring framework 101
Simplilearn
June 23, 2026 – Present
Introduction to Generative AI Studio
Simplilearn
June 23, 2026 – Present
JavaScript
HackerRank
June 23, 2026 – Present
SQL Basic
HackerRank
June 23, 2026 – Present
Java Basics
HackerRank
June 23, 2026 – Present
Cultural Fit Analysis
The candidate demonstrates a strong inclination towards cutting-edge technologies, particularly in AI and distributed systems, which suggests a fit for innovative and fast-paced environments. The diversity of personal projects (AI job portal, payment engine, ride-sharing platform) indicates a broad interest in different problem domains and a drive for continuous learning. The target role of 'Backend Engineer' aligns well with the candidate's demonstrated technical depth in backend frameworks and system design. However, the candidate's experience level is listed as 1, which might indicate a mismatch for senior-level roles requiring extensive industry experience, despite the advanced nature of personal projects.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive and innovative approach to problem-solving, particularly in designing complex systems like the AI Job Matchmaker and payment engines. The focus on 'Agentic AI' and 'autonomous workflows' suggests an ability to think beyond conventional solutions and drive automation. However, without direct assessment data, specific soft skills like teamwork, communication, and stress handling cannot be objectively evaluated.