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
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
- Ultimate CKAD Certification Guide — OrangeAva
- Modern API Design with gRPC — OrangeAva
- Flash talk — gRPC Load Balancing @ GopherCon 2023
- Virtual talk — Microservice Communication using gRPC @ AWS UG Bangalore
- Blog featured in kube-weekly
- Blog featured in LearnK8s LinkedIn pulse
- 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
.ndjsonKibana 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)
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
I'm diving into the intricacies of retrieval-augmented generation (RAG) by implementing a hybrid approach that leverages both traditional vector embeddings and modern vector databases for optimizing information retrieval in knowledge-heavy applications. Specifically, I'm exploring how to efficiently manage and query large-scale datasets while minimizing latency, focusing on integrating ANN algorithms with chunking techniques to enhance the accuracy of the retrieval process. Additionally, I'm evaluating the impact of context-aware AI interaction models on improving user engagement in chat assistants.
Powered by Claude via scheduled GitHub Actions · view workflow



