AI Engineer with less than a year in Multi-Agent Orchestration, RAG, and Python.
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Assessing your cultural and operational fit
Highly motivated and skilled AI Engineer with hands-on experience in developing AI-native knowledge workspaces, multi-agent pipelines, and security operations platforms. Proficient in Python, TypeScript, and various AI/ML frameworks. Successfully delivered projects involving real-time anomaly detection, intelligent legal document assistance, and cost optimization, demonstrating strong problem-solving and technical implementation capabilities.
VIT Bhopal University
Bachelor of Technology · Computer Science Engineering
August 1, 2022 – June 30, 2026
Memfold AI
AI Intern
January 1, 2026 – February 1, 2026
India
Sentinel-MCP - AI-Powered Security Operations
May 1, 2026 – Present
Built a production-grade SOC MCP server that lets security analysts investigate alerts, threat intel, identity and endpoint data directly inside Claude Desktop exposing 18 MCP tools over 15 integrated security backends (OpenSearch, Keycloak, VirusTotal, MITRE ATT&CK etc.), reducing the need to context-switch across tools. Designed a fault-tolerant integration layer in async Python (httpx) with circuit breakers, automatic retries and distributed tracing, ensuring a single slow or failing backend never stalls an active investigation. Hardened every high-risk action behind OAuth 2.1 + PKCE, default-deny authorization policies (OPA), a SHA-256 hash-chained audit log, and a two-step confirmation safeguard on all destructive operations. Packaged the project into a release-ready v1.0.0 for the Claude marketplace, with 497 automated tests at ~95% coverage and a fully containerized Docker Compose stack enabling one-command local setup.
View ProjectLogWatch - AI-Powered Log Anomaly Detection SaaS
March 1, 2026 – April 1, 2026
Published a Node.js SDK that gives any service real-time anomaly detection in just 2 lines of code, helping teams catch production incidents within 20s without setting manual thresholds - backed by a 5s log batch flush that cuts HTTP requests by ~90%. Shipped a 5-stage streaming pipeline across a TypeScript SDK, Spring Boot (Java 21) API, Kafka, Rust/Tokio engine, PostgreSQL, and React dashboard, capturing every request by patching http.Server.prototype.emit. Scored a rolling 7-feature window with an ONNX IsolationForest model trained on 52,632 samples to flag anomalies, paired with a Groq llama-3.3-70b assistant that explains each one in plain English. Containerized all services with Docker behind a multi-job CI pipeline that runs Rust and Spring Boot tests on every push, then publishes versioned images to GHCR for automated deploys to Railway, Neon and Vercel.
View ProjectLawgorithm - Intelligent Legal Document Assistant
January 1, 2026 – March 1, 2026
Created an AI legal assistant that lets non-lawyers query complex legal documents in plain English, using a self-correcting RAG pipeline that grounds every answer in source text with a confidence score, for verifiable responses. Architected a 6-node LangGraph agentic workflow with up to 3 self-correction loops and dual swappable LLMs (Groq Llama-3.3-70B + Google Gemini), combining HyDE query enhancement and Pinecone retrieval stack. Delivered a FastAPI backend (3 REST endpoints) and Streamlit UI with live reasoning traces, benchmarking a ~35% drop in hallucinated answers across 50 queries, with 18 automated tests and a GitHub Actions CI/CD pipeline.
View ProjectFinalist, DeepBlue Hackathon
Unknown
June 1, 2026 – Present
IBM AI Engineering Professional Certificate
IBM
June 1, 2026 – Present
IBM Cybersecurity Certificate
IBM
June 1, 2026 – Present
NPTEL Marketing Analytics (Elite Silver)
NPTEL
June 1, 2026 – Present
Ranked Top 2% (National) in NPTEL Cloud Computing (IIT Kharagpur)
NPTEL (IIT Kharagpur)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including AI-powered security, log anomaly detection, and legal assistance, showcases a broad interest in applying AI across different domains. Their involvement in hackathons and NPTEL certifications indicates a proactive learning attitude. The leadership roles in university clubs suggest a collaborative and community-oriented mindset. The target role of 'AI Engineer' aligns well with their demonstrated technical skills and project focus.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and project ownership through multiple personal projects. Their involvement in organizing events and leading social media strategy suggests good organizational and teamwork skills. The focus on building production-grade systems and automated testing indicates an operational mindset. However, the limited professional experience (one short internship) means these soft skills are primarily inferred from project descriptions rather than direct professional application.