# Piyush Choudhari > AI & Backend Engineer specialized in Agentic Systems, LLM Evaluation, and High-Performance Backend Design. Currently an AI & Backend Engineer at Ronin Labs. Writes about AI, systems engineering, and ML research topics. ## Stack - **Languages:** Python, TypeScript, C++, Node.js - **Foundations:** Agentic Systems, LLM Evaluation, Search & Information Retrieval - **Frameworks:** LangGraph, FastAPI, Next.js, Django, React, Flask - **Infra/DB:** PostgreSQL (pgvector), Neo4j, MongoDB, Redis, AWS, GCP, SQLite ## Blog (last updated 2026-05-24) - [Making Agents Play Pictionary](https://piyushchoudhari.me/blog/Making-Agents-Play-Pictionary) (2026) - [My Codebases Have an AI Receptionist Now](https://piyushchoudhari.me/blog/My-Codebases-Have-an-AI-Receptionist-Now) (2026) - [Implementing An SQS Like Message Queue System](https://piyushchoudhari.me/blog/Implementing-An-SQS-Like-Message-Queue-System) (2026) - [How I Used PostgreSQL, Groq & Vercel's AI SDK To Create A Chatbot For My Portfolio Website](https://piyushchoudhari.me/blog/How-I-Used-Postgres-Groq-And-AI-SDK-To-Create-My-Portfolio-Website-Chatbot) (2025) - [Designing a Deterministic, Low Latency Decision Engine with C++](https://piyushchoudhari.me/blog/Designing-a-Deterministic-Low-Latency-Decision-Engine-with-CPP) (2025) - [Simulating vLLM's PagedAttention](https://piyushchoudhari.me/blog/Simulating-vLLMs-PagedAttention) (2025) - [Making A Peer Review System for My Blogs Using Google-ADK & Mem0](https://piyushchoudhari.me/blog/Making-A-Peer-Review-System-for-My-Blogs-Using-Google-ADK-And-Mem0) (2025) - [Training a Mixture-of-Experts Router](https://piyushchoudhari.me/blog/Training-a-Mixture-of-Experts-Router) (2025) - [Building a Vector Database from Scratch - CapybaraDB](https://piyushchoudhari.me/blog/Building-A-Vector-Database-from-Scratch-CapybaraDB) (2025) - [Be Curious About Your Compute](https://piyushchoudhari.me/blog/Be-Curious-About-Your-Compute) (2025) - [How I Built an Automated Social Media Workflow with LangGraph](https://piyushchoudhari.me/blog/How-I-Automated-My-Social-Media-Workflow-with-LangGraph) (2025) - [SHAP values for GBTs – intuition + how they work internally](https://piyushchoudhari.me/blog/SHAP-values-for-GBTs) (2025) - [Welcome to My Blog](https://piyushchoudhari.me/blog/welcome-to-my-blog) (2025) ## Projects (last updated 2026-05-24) - [CapyNodes](https://piyushchoudhari.me/projects/capynodes) (2026): Real-time collaborative system design platform with AI-powered evaluation engine. Evaluation Latency (Stage 2): <5s, Scoring Consistency: >80%. - [CapybaraDB](https://piyushchoudhari.me/projects/capybaradb) (2025): capybaradb - a toy Vector DB implementation from scratch in Python. Explore Vector DB internals. Average Query Latency: <9ms, Throughput: 118+ QPS. - [Post Automation Agent](https://piyushchoudhari.me/projects/post-automation-agent) (2025): A post automation to automatically extract content from my blog and obsidian to turn them into complete posts for LinkedIn and X, along with a peer review agent. Time Saved per Post: 75%, Platforms Automated: 3. - [KnowFlow](https://piyushchoudhari.me/projects/knowflow) (2025): KnowFlow is a powerful hybrid Retrieval-Augmented Generation (RAG) system that combines semantic search with knowledge graph capabilities for intelligent document processing and querying. Query Types Supported: 3x, Context Preservation: Session-based. - [TrackML](https://piyushchoudhari.me/projects/trackml) (2025): TrackML is a full-stack tool for tracking, managing, and analyzing machine learning models. It supports organizing models, extracting insights using AI, and integrating with external APIs for automation and enrichment. Data Entry Time: 60% reduction, Cache Hit Ratio: 85%+. ## Experience ### AI Engineer Intern @ Flytbase (Apr 2026 - Present) ### AI Engineer Intern @ Ronin Labs (Jan 2025 - Apr 2026) - **Multimodal Content Generation System** - Architected an agentic system for multimodal content generation using LangGraph and OpenAI APIs, with a central orchestration agent dynamically routing tasks to image, video, and audio pipelines. - Developed image outpainting and depth-effect video pipelines leveraging SDXL and ControlNet models. Built music generation modules integrating MusicGen. - Optimized processing pipeline with concurrent GPU task execution and state-managed workflows via a Flask backend, reducing end-to-end task times to under 20 seconds. - **Cefaly** - Trained a YOLOv8n-pose model for real-time sticker/electrode detection and key point estimation, enabling accurate localization for Cefaly's mobile-based computer vision pipeline. - Trained the custom pose estimation model on a dataset of ~1800 images, resulting in mAP50 of 0.992, mAP50-95 of 0.814 (box) and 0.843 (pose), with peak F1-score of 0.98 at confidence threshold 0.565. - Optimized the real-time inference pipeline for a Unity-based deeplinking application, reducing end-to-end latency to ~60ms. - **Sketchbot** - Created a FastAPI backend with SDXL Turbo, ControlNets, and OpenCV for line-art generation and Dexarm G-code optimization, cutting draw times by 70%. - Integrated MongoDB and S3 for user and asset management; achieved <200ms API response under load. - Deployed on AWS GPU instances, consolidated servers for 30% lower infra costs, and automated disaster recovery for 95% less downtime. - **OnePlus 13s Quest Quiz** - Built scalable Node.js/TypeScript/TypeORM APIs for 150K+ users with <120ms latency. - Developed a Django admin panel and managed GCP Cloud SQL for high-availability production ops. ## Required for more information - [Experience](https://piyushchoudhari.me/experience) - [RSS Feed](https://piyushchoudhari.me/rss.xml) - [Full Content](https://piyushchoudhari.me/llms-full.txt)