HiteshRepo - Overview

Hi, I'm Hitesh 👋

Hitesh Pattanayak | LinkedIn Hitesh Pattanayak | Medium

Senior Software Engineer with 10+ years building scalable data pipelines, cloud-native infrastructure, and enterprise backend systems. Currently working on indexing and searching petabytes of M365 data.

🌐 hiteshpattanayak.info · AWS Community Builder · CKAD Certified


🛠 Tech Stack

Languages: Go · Python · TypeScript / Node.js · PySpark
Data Engineering: Databricks · Apache Spark · Delta Lake · Azure Event Hubs
Cloud & Infra: Kubernetes · Docker · Azure · AWS · Terraform · Pulumi
Databases: CosmosDB · PostgreSQL · Elasticsearch · TimescaleDB
AI / LLM: RAG pipelines · Azure OpenAI · Anthropic API · Vector Search
Protocols & APIs: gRPC · REST · GraphQL


📚 Books


🎤 Talks & Features


🤖 AI Work

  • Semantic Search (RAG) — CosmosDB hybrid vector search + Azure OpenAI over petabytes of M365 backup data; natural language → metadata filters via few-shot Chat Completions
  • Elastic Dashboard Changelog — Python + Anthropic API tool that diffs unreadable .ndjson Kibana files and generates human-readable changelogs
  • Security Fix Automation — LLM-assisted local skill that ingests Cycode findings and applies targeted fixes with full code context
  • Blog Generator — AI-powered workflow (Claude / OpenAI) to draft posts from structured idea files
  • AI Chat Assistant — RAG conversational assistant on my blog site (TF-IDF + Netlify Functions + GPT-4o-mini)

💬 Try the AI Assistant

My blog has a built-in AI chat assistant. Ask it about my posts, projects, or background — it retrieves relevant content and answers using GPT-4o-mini.

👉 Chat at hiteshpattanayak.info


🧠 Currently Thinking About

I'm delving into optimizing retrieval-augmented generation (RAG) architectures, particularly focusing on how to effectively leverage vector databases for enhanced performance in hybrid search scenarios. I'm also exploring advanced chunking techniques to balance the trade-off between context granularity and processing efficiency, which is crucial for maintaining relevance in AI chat applications. Integrating these methodologies with page-aware context retrieval to improve user interactions is a key area of interest right now.

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