Aspiring Software Engineer

Backend Focused.

I build reliable backend systems, secure APIs, and practical AI-enabled tools that solve real problems.

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About

Hi, I am Ashutosh!

I am a passionate computer science student and software developer with a deep interest in building intelligent, scalable systems that solve real-world problems.

My journey in tech is fueled by a strong foundation in data structures and algorithms, which I have honed through consistent practice and competitive programming.

I am also an avid builder of projects. From a competitive programmer to a developer, I enjoy working across the stack, whether it is backend development with Python (Flask) or integrating machine learning models.

I am always open to connecting, collaborating, and discussing new opportunities in software engineering and AI.

Skills

Python Flask FastAPI SQLAlchemy PostgreSQL Databases REST API Security Scalability JWT RBAC 2FA Socket.IO Redis Redis Pub/Sub Celery Docker CI/CD GitHub Actions Machine Learning RAG ChromaDB MLflow Streamlit C++ Data Structures HLD LLD

Projects

Collaborative Task Management Platform

  • Designed scalable system architecture using HLD and LLD principles for modular and maintainable development.
  • Implemented secure authentication using JWT with role-based access control (RBAC).
  • Integrated two-factor authentication (2FA) for enhanced account security.
  • Built real-time task updates using Socket.IO for instant synchronization across users.
  • Used Redis Pub/Sub to support real-time communication and event handling.
  • Developed RESTful APIs using Flask and PostgreSQL for efficient backend operations.
  • Implemented asynchronous background processing using Celery and Redis.
  • Handled background jobs such as notifications and heavy tasks efficiently.
  • Applied security measures including input validation, rate limiting, and secure headers.
  • Containerized the application using Docker for consistent deployment.
  • Set up CI/CD pipeline using GitHub Actions for automated testing and deployment.

Intelligent IT Operations Assistant

  • Built an AI-powered system using retrieval-augmented generation (RAG) architecture.
  • Enabled natural language querying for incident data analysis.
  • Implemented semantic search using vector embeddings with ChromaDB.
  • Developed root cause analysis to identify patterns in incidents.
  • Integrated anomaly detection for identifying unusual trends.
  • Designed backend services using FastAPI.
  • Created a simple interface using Streamlit.
  • Integrated MLflow for experiment tracking.
  • Containerized the application using Docker.

Coding Profiles

GitHub LeetCode HackerRank CodeChef Codeforces