Mordheesh B
Junior Software Developer | Full Stack & AI Engineer
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About
Detail-oriented Junior Software Developer specializing in building scalable cloud microservices, real-time AI workflows, and enterprise data solutions. Proficient in Python, Java, SQL, FastAPI, Next.js, and AWS platforms, with practical focus on Databricks data pipelines and API integrations. Proven track record of delivering reliable systems achieving 99.9% uptime and optimizing data processing workflows by over 40%.
Experience
Junior Full Stack AI Developer - Nivora AI
(2025-01 - 2026-12)
Autonomous Executive Workspace
- Developed an automated document extraction engine using PyMuPDF and Tesseract OCR, reducing manual review time by 40%.
- Implemented a WebSocket real-time engine delivering sub-200ms processing latency across 50+ concurrent active user sessions.
- Architected a modular microservices platform with Vue.js 3, Pinia, and Vite backed by a high-throughput FastAPI service layer.
- Engineered an Agentic RAG pipeline using LangChain, LangGraph, ChromaDB, and Google Gemini API, increasing retrieval accuracy by 25%.
Junior Cloud Software Developer - AI-Powered Cloud Security Auditor Platform
(2025-01 - 2026-12)
- Built a multi-tenant auditing dashboard utilizing Next.js, FastAPI, and PostgreSQL to track real-time security compliance for 100+ endpoints.
- Automated credential-free cross-account access via AWS STS AssumeRole and Boto3, generating compliance reports across 7 global frameworks.
- Integrated Model Context Protocol orchestration with embedded policy guardrails, reducing unverified system operations to 0%.
Cloud & Backend Engineer - Cloud-Based AI Resume Role Prediction System
(2026-01 - 2026-01)
- Developed a serverless machine learning platform parsing unstructured resume data to calculate job-matching fit scores within 1.5 seconds.
- Created RESTful microservices with AWS Lambda and API Gateway, establishing zero-trust access control via AWS IAM and Amazon S3.
- Configured automated AWS CloudWatch monitoring and auto-scaling rules, achieving 99.9% platform availability during peak load testing.
Machine Learning Developer - Student Result Prediction Dashboard
(2024-05 - 2024-05)
- Built supervised classification models in Scikit-Learn to forecast student academic outcomes, achieving 88% prediction accuracy.
- Executed data preprocessing and feature scaling on 5,000+ records using NumPy, Pandas, and Matplotlib.
Education
B.Tech - Artificial Intelligence & Data Science - Sri Manakula Vinayagar Engineering College (2023-01 - 2027-12)
