Shamik Munjani

Software Engineer Intern

Surat, Gujarat, India 394326Software Engineering and Artificial Intelligence
1roles
34skills
1education

About

Computer Science Engineering student with software engineering internship experience in Python, observability, backend development, AI/ML systems, testing, and CI/CD.

Experience

Software Engineer Intern

Crest Data Systems

December 2025 – May 2026 · Ahmedabad, Gujarat

Developed a Python-based Datadog integration for remote VM environments, including observability monitors, dashboards, detection rules, and reliability improvements. Built unit, functional, and end-to-end tests for monitor execution, pipeline parsing, and detection-rule triggering, including AI-assisted functional testing workflows using Claude skills.md. Automated testing and deployment pipelines with GitLab CI, Docker, and DDEV-based environments.

Education

Institute of Technology, Nirma University

B.Tech., Computer Science Engineering

2022 – 2026

CGPA: 8.4/10; Ahmedabad, Gujarat

Skills

PythonJavaScriptSQLFastAPINode.jsReact.jsREST APIsPostgreSQLRedisEnsemble LearningGenerative AIRAGAgentic AILLMsLangChainLangGraphFastMCPFAISSHuggingFaceTensorFlowGitGitHub ActionsCI/CDDockerDatadogBashObservabilityMachine LearningFeature EngineeringC++TA-LibCCXTGoogle GeminiDDEV

Projects

InvestIQ — ML Based Crypto Trading Platform

Engineered an ensemble ML system using XGBoost, LightGBM, and Random Forest that achieved 78% accuracy for crypto price prediction. Built a full-stack application with FastAPI and React.js for real-time trading insights and implemented automated retraining APIs using 10+ technical indicators with TA-Lib and CCXT.

Tripster — AI-Powered Multi-Agent Travel Planner

Designed an intelligent travel platform using LangGraph, LangChain, and advanced LLM models. Orchestrated an 8-agent system for autonomous itinerary generation and built a scalable asynchronous FastAPI backend with Redis caching, remote MCP server integration, and a React.js dashboard.

YTChat — RAG-Based AI YouTube Video Assistant

Built a RAG-based YouTube assistant using LangChain, FAISS, and Sentence-Transformers for semantic transcript search. Developed a FastAPI backend with Google Gemini for real-time video Q&A and a Manifest V3 Chrome extension with transcript ingestion and HuggingFace embeddings.