Seshank Rakshit

I’m a computer science undergraduate with hands-on SOC operations experience, focused on turning messy security signals into faster, repeatable decisions. I combine security monitoring with AI system thinking to improve how teams detect, investigate, and respond.

In my SOC Analyst Intern role, I monitored and triaged security alerts and system logs using SIEM tools to detect anomalies and potential threats. I investigated incidents through log analysis and threat correlation, then documented structured triage workflows to improve SOC response repeatability. I’ve worked with Rapid7, SentinelOne, Falcon XDR, ThreatConnect, and Sysdig, using Wireshark and Nmap during investigations.

I also build AI systems—especially agentic pipelines and RAG architectures—to support real operational outcomes. I created a stateful agentic chatbot using LangGraph and LangChain with interchangeable LLM providers, and I built a RAG-based knowledge base chatbot using document ingestion, chunking, embeddings in ChromaDB, and retrieval scoring to reduce hallucinations.

Right now, I’m designing an AI-powered security alert triage pipeline that uses LangChain and RAG to auto-contextualize and prioritize SIEM alerts. My goal is to reduce manual triage time while keeping outputs structured for SOC dashboard consumption through a FastAPI backend.