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  • Joined Apr 13, 2026

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pvenkata-tech/README.md

Venkata Pagadala 👋

Staff Software Engineer & AI Lead

15+ Years of Systems Architecture | Specialist in Agentic RAG & Stateful LLM Orchestration

I bridge the gap between "experimental AI" and "production-ready systems." I architect autonomous, resilient AI agents that solve complex business logic problems with a focus on reliability, observability, and cost-efficiency.


📈 Current Technical Focus

  • 🛠️ Refining Agentic Workflows: Optimizing state-graph transitions and Human-in-the-Loop refinement patterns in LangGraph.
  • 🧪 LLMOps & Resiliency: Implementing automated evaluation frameworks (Ragas/LangSmith) to ensure 1.00 Faithfulness for non-deterministic outputs.
  • 🌐 AEO/GEO: Developing high-performance utility tools optimized for the Generative Search era (AEO/GEO), focusing on latency and structured data.

🏆 Featured Project: Agentic Deep Research Assistant

🔗 View Repository My flagship project demonstrating Production-Grade Agentic RAG.

  • The Problem: Standard RAG chains are linear and prone to hallucinations when context is missing.
  • The Solution: A cyclic, stateful multi-agent system built with LangGraph and Ollama.
  • Key Innovation: Implemented a Human-in-the-Loop (HITL) persistence layer using SQLite, allowing complex research tasks to be paused, reviewed, and refined without state loss.
  • Engineering Edge: Features asynchronous parallel search, Pydantic-validated state schemas, and structured observability.

🩺 Domain Expertise: Clinical Intelligence

🔗 View Project

  • Architecture: Utilizes AWS Bedrock and Pinecone to maintain strict healthcare compliance while extracting medical insights.
  • Focus: Intelligent parsing and PII scrubbing of clinical documents for secure inference.

🛠️ Technical Arsenal

Category Stack
AI Orchestration LangGraph (Stateful Agents), LangChain, Multi-Agent Workflows
LLMs & RAG Ollama (Local), AWS Bedrock, OpenAI, RAG Pipeline Optimization, LLMOps
Data & Search Pinecone (Vector DB), Tavily (Search API), PostgreSQL, Redis
Core Engineering Python, FastAPI, TypeScript, React, Docker, AWS (ECS & Lambda)

⚡ Professional Philosophy: "Safe AI"

I believe the future of AI in the enterprise isn't fully autonomous—it's collaborative. I specialize in building Human-in-the-Loop architectures that ensure AI outputs remain accurate, ethical, and aligned with business objectives.

📫 Let's Build Something Resilient

  • LinkedIn: /in/pvenkata-tech
  • Location: Austin, TX / Remote
  • Contract Focus: Senior/Staff AI Engineering & LLM Systems Architecture

Pinned Loading

  1. agentic-deep-research-graph agentic-deep-research-graph Public

    A stateful multi-agent system for autonomous deep research with Human-in-the-Loop refinement, powered by LangGraph and local LLMs.

    Python

  2. clinical-intelligence-rag clinical-intelligence-rag Public

    Enterprise-grade Clinical RAG pipeline with multi-provider support (Bedrock, OpenAI, Anthropic) and automated Pinecone indexing.

    Python

  3. sentinel-ai-gateway sentinel-ai-gateway Public

    A high-performance, streaming-first AI Observability & Guardrail Proxy. Intercept, redact (PII/PHI), and monitor LLM traffic in real-time with zero-latency overhead. Built with FastAPI, Pydantic v2…

    Python