---
title: "Shivam Govind Rao - Software Development Engineer in Gurugram | Tal"
description: "Meet Shivam Govind Rao, AI Engineer | LLM Systems, RAG, Agents (LangGraph, LangChain) | AWS Bedrock | TypeScript, Python, React | Built 0 to 1 AI Healthcare Platform (Ex-Diagna AI) based in Gurugram. AI stack includes claude code, codex, and langchain. Explore public work links including github and..."
image: "https://tal.club/meet/shivam-govind-rao/share-image"
---

# Shivam Govind Rao on Tal

## Headline

AI Engineer \| LLM Systems, RAG, Agents \(LangGraph, LangChain\) \| AWS Bedrock \| TypeScript, Python, React \| Built 0 to 1 AI Healthcare Platform \(Ex\-Diagna AI\)

## About

AI Engineer with 2\.5 years of experience building production LLM systems end to end: RAG, multi\-agent workflows, and the backends and frontends around them\. Highlights • Built the document\-AI platform at Diagna AI \(HIPAA\-compliant\) that classifies and extracts data from 1,000\+ medical documents/day across 40\+ categories for live US clinics, using Claude, Amazon Nova and Llama on AWS Bedrock • Cut manual fax triage from about 3 hours to 10 minutes a day and referral turnaround from 4\.2 days to same day • Shipped VoiceGenie, a generative\-AI voice sales platform, from 0 to $10K MRR in 11 months as the sole frontend engineer What I work on • LLM systems: structured outputs, model routing and fallbacks, grounding, human\-in\-the\-loop review, evals • Agents and RAG: LangGraph, LangChain, hybrid retrieval \(FAISS \+ BM25\), RAGAS • Distributed backends: AWS \(S3, SQS, SNS, Bedrock\), BullMQ/Redis, PostgreSQL, idempotent pipelines • Product frontends: React, Next\.js, TypeScript Projects • PayOps AI: 19\-node LangGraph multi\-agent system for payment reconciliation, with parallel agents, Postgres checkpointing, four\-eyes approval and 7/7 golden evals passing • ClinRAG: hybrid RAG over FDA drug labels with a RAGAS eval harness • MotionStudio: browser video editor with in\-browser and cloud \(Remotion on AWS Lambda\) export Stack: Python, TypeScript, Node\.js, FastAPI, React, Next\.js, AWS Bedrock, LangGraph, LangChain, PostgreSQL, Redis, Docker Open to AI Engineer / GenAI roles\. Reach me at ishivamgovindrao@gmail\.com

## Location

Gurugram

## AI stack

claude code

codex

langchain

langgraph

livekit

mcp

## Work experience

Software Development Engineer at Diagna, Jan 2025 \- Apr 2026 · 1 yr 4 mos, Gurugram, Haryana, India, • Architected and owned the core backend of a HIPAA\-compliant clinical document platform serving live paying clinics: 40\+ REST endpoints \(TypeScript, Express, JWT \+ RBAC, Swagger\) over a 25\-model PostgreSQL/Prisma schema • Integrated Claude, Amazon Nova and Llama via AWS Bedrock to classify and extract structured data from 1,000\+ medical faxes/day across 40\+ document categories, with model fallback, retries and schema\-validated JSON output • Cut manual fax triage from about 3 hours to 10 minutes a day and cleared a recurring 2\-day backlog by chaining AI extraction, patient matching, human review and EHR write\-back • Engineered the distributed AWS ingestion pipeline \(S3, SQS, SNS\) with 7 BullMQ/Redis queues, DB\-level idempotency and a dead\-letter queue that self\-healed transient failures • Built human\-in\-the\-loop safety: ambiguous patient matches routed to review instead of overwriting records, with transactional writes and AI\-extraction lineage • Automated a no\-API legacy EHR \(MDLand\) with a Python RPA service \(FastAPI, Robocorp, Playwright, Redis/RQ\) plus Medplum FHIR sync, cutting referral turnaround from 4\.2 days to same day • Delivered both production React 19 frontends: the FAXFlo clinical inbox with a dual\-view AI document editor \(Zustand, PDF\.js\) and an internal patient\-record merge dashboard

Software Engineer at Oriserve, Dec 2023 \- Jan 2025 · 1 yr 2 mos, Hybrid, • Built VoiceGenie, a generative\-AI voice sales platform, from 0 to 1 as the sole frontend engineer \(Next\.js, React, TypeScript\): customer dashboard, AI campaign builder, onboarding and post\-call analytics; the product reached $10K MRR within 11 months and closed its first enterprise customers • Built per\-campaign ElevenLabs voice controls and an @token script composer that personalized every AI call at runtime • Shipped post\-call AI intelligence \(transcripts, emotion analysis, lead extraction\) synced to HubSpot and GoHighLevel, with Cal\.com booking • Integrated Stripe payments end to end \(checkout UI, backend APIs, transaction\-state handling\) • Cut page load time by 30% \(LCP, FCP, TBT, CLS\) through Lighthouse profiling, code splitting, lazy loading and caching • Collaborated on Twilio voice\-AI infrastructure for 2K\+ concurrent calls and rate limiting that blocked 15K\+ abusive requests/day

## Education

Bachelor of Technology \- BTech, Computer Science and Engineering, Institution of Engineering and Technology Ayodhya

## Public links

- github: https://github\.com/BLAZE7SHADOW
- shivamgovindrao\.com: https://www\.shivamgovindrao\.com/

[View the original profile](https://tal.club/meet/shivam-govind-rao)

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