Rudra P.

# AI Engineer | RAG, Agents, FastAPI, Next.js | AI Automation I help businesses **turn ideas and real-world problems into production-ready AI applications, agentic systems, and intelligent automation.** Whether you need to **build an AI product from scratch, add AI capabilities to an existing application, automate a complex workflow, or improve an unreliable RAG/agent system**, I can take the problem from: **Idea → Architecture → Development → Deployment → Evaluation → Production** I build AI systems designed to work as **real software products — not just prototypes or LLM demos.** --- ## 🚀 What I Build **RAG & AI Knowledge Systems** * Knowledge assistants * Document Q&A * Semantic & hybrid search * Embeddings & vector search * Grounded responses and citations * Retrieval optimization **AI Agents & Agentic Systems** * Tool-using agents * Multi-step workflows * LangGraph-based agent systems * Structured outputs * Human-in-the-loop workflows * Controlled task execution **AI Automation** * Intelligent business workflows * API integrations * Document processing * AI-powered internal tools * Repetitive task automation * Workflow orchestration **LLM-Powered Applications** * AI copilots * Conversational applications * AI features inside SaaS products * AI-powered business applications * Custom LLM integrations **AI Backend Systems** * Python / FastAPI * Async APIs * PostgreSQL * Redis * Background workers * REST APIs * Server-Sent Events (SSE) * Authentication, RBAC & multi-tenancy **AI Evaluation & Reliability** * Evaluation datasets * Retrieval evaluation * LLM-as-a-judge * Regression testing * Tracing & observability * Failure analysis * AI quality improvement --- ## ⚙️ I Build the System Around the AI — Not Just the AI A production AI application needs much more than an LLM API. I design and implement the surrounding engineering system: **APIs · Databases · Authentication · Authorization · Background Workers · Queues · Caching · Vector Search · Tool Integrations · Agent Orchestration · Streaming · Error Handling · Observability · Evaluation · Deployment** For **agentic systems**, I focus on controlled execution and reliability: * Bounded workflows * Structured state * Typed tools * Validation * Retries and failure handling * Human approval where appropriate * Deterministic handling of critical business data For **RAG systems**, I focus on measurable retrieval and answer quality rather than simply connecting a vector database to an LLM. I can work across: **Ingestion → Chunking → Embeddings → Retrieval → Reranking → Prompting → Evaluation → Monitoring** The goal is to understand **where the system is actually failing** and improve that specific layer. --- ## 🧠 Recent AI Systems I've Built ### AI Second-Brain / Knowledge Platform A multi-tenant AI knowledge platform built with: **FastAPI · PostgreSQL · Redis · Qdrant · LangGraph** The system includes: * Workspace-level RBAC and tenant isolation * Document ingestion * Background processing * Embeddings and retrieval * RAG conversations * Agentic workflows * Human-in-the-loop controls * Streaming responses * AI evaluation * Tracing and observability * Rate limiting * Production deployment --- ### Agentic Travel Planning Platform A full-stack AI travel planning system built with: **Next.js · FastAPI · LangGraph · Qdrant** The system combines: * Hybrid retrieval * Deterministic route and itinerary planning * Tool-based agent orchestration * External geo/routing services * Structured trip persistence * Streaming generation * Evaluation A key architectural principle is separating **deterministic business logic from probabilistic LLM reasoning**. Places, coordinates, routes, ordering and schedules are controlled by application logic rather than being blindly generated by an LLM. The LLM is used where it provides real value: **Reasoning · Orchestration · Natural-language generation** --- ## 🛠️ Engineering Foundation I come from a strong software engineering background, which I bring into AI development. **Backend** Python · FastAPI · Async APIs · PostgreSQL · SQLAlchemy · Redis · Background Workers · REST APIs **AI** LLM Applications · RAG · Embeddings · Vector Databases · LangGraph · Tool Calling · Agent Workflows · Structured Outputs · AI Evaluation · Observability **Frontend** Next.js · React · Streaming AI Interfaces **Production** Docker · CI/CD · AWS EC2 · AWS Bedrock · Managed Infrastructure · Logging · Monitoring · Deployment --- ## 🎯 I Can Help If You Are... → Turning an **AI product idea into a working production application** → Building a **RAG or knowledge assistant** that needs better retrieval and answer quality → Developing an **AI agent** that needs reliable tool use and controlled workflows → Automating a **manual business process with AI and API integrations** → Adding **AI capabilities to an existing SaaS or web application** → Debugging an **AI system that works in demos but behaves