AI/ML Engineer (final-year B.Tech, AI & Data Engineering @ LPU), currently an AI Engineering Intern working on LLM Systems & Applied GenAI β building production-grade agentic pipelines with LangGraph, open-weight LLMs, and full observability.
- Building EquityFlow, a multi-agent equity research system (LangGraph, Llama-3.1-8B, Tavily, yfinance, ChromaDB, FastAPI, LangFuse).
- Author of AutonoML v2.3.0, a multi-agent AI platform β Planner (DAG), parallel Research, ReAct Execution, hybrid LLM + programmatic Evaluation, two-tier memory, 386 tests; SmartRouter cuts latency from ~45s β ~2s on direct queries.
- Previously built data/AI pipelines at Futurense Technologies.
- Shipped AIOps RCA (XGBoost + SHAP + FastAPI + Docker) and a serverless Model Arbitration Engine on AWS (87ms avg latency across sklearn / XGBoost / Bedrock).
- Interests: LLM orchestration & agents, RAG evaluation, MLOps/AIOps, GPU-poor-friendly open-source model engineering.
| Languages |
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| AI / ML & GenAI |
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| Data & Backends |
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| Cloud & DevOps |
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- Building multi-agent LLM systems (research, writer, and critic agents) with real LLM calls, web research, financial data tooling, and persistent memory.
- Instrumenting pipelines end-to-end with LangFuse tracing and eval hooks for reproducible agent behaviour.
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- Integrated and cleaned 5+ MBA admissions datasets using Python (Pandas), performing data preprocessing and exploratory data analysis to uncover campaign and enrollment insights.
- Developed a multi-page Power BI dashboard to visualize KPIs, marketing funnel performance, applicant analytics, and campaign ROI for data-driven decision-making.
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| Project |
Description |
Stack |
| EquityFlow Β· Multi-Agent Equity Research |
Multi-agent equity research system β research, writer, and critic agents over live web + financial data with persistent memory and full tracing. |
LangGraph Llama-3.1-8B ChromaDB FastAPI LangFuse |
| AutonoML Β· Multi-Agent AI Platform |
Planner (DAG) + parallel Research + ReAct Execution + hybrid LLM/programmatic Evaluation; two-tier memory, self-reflection loop, 386 tests; SmartRouter: ~45s β ~2s on direct queries. |
FastAPI Streamlit ChromaDB Ollama/Groq |
| LoopForge Β· Agentic Loop Platform |
LangGraph multi-loop agentic platform with distributed task execution and production observability. |
LangGraph Celery Redis PostgreSQL LangFuse |
| AIOps RCA System Β· Root Cause Analysis |
XGBoost root-cause classifier over LEMMA-RCA incidents β 96 features, 6 classes, SHAP explainability, cascade-risk detection, Go/No-Go deployment gate. |
XGBoost SHAP FastAPI PostgreSQL Docker |
| Model Arbitration Engine Β· AWS Serverless |
Real-time router across sklearn / XGBoost / Bedrock Haiku β epsilon-greedy + EMA latency tracking; 87ms avg latency at 95.3% accuracy. |
AWS Lambda SageMaker Bedrock DynamoDB |
| Ollive Β· LLM Assistant Benchmark |
Llama-3.1-8B vs Llama-3.3-70B benchmark with LLM-as-judge scoring, 4-layer guardrails, and LangFuse v4 tracing; deployed on Render + HF Spaces. |
Groq LangFuse Streamlit Render |
AI/ML Engineer in the making Β· B.Tech AI & Data Engineering @ LPU Β· ex-Futurense Β· Agentic AI, LLM Systems & MLOps