---
title: "Geetha Pardheev Chunduru - Founding Engineer in Bengaluru | Tal"
description: "Meet Geetha Pardheev Chunduru, Voice AI & Distributed Systems | Ex-Amazon | Ex-Toyota Connected | IIT Kharagpur based in Bengaluru. AI stack includes claude code, claude, and codex."
image: "https://tal.club/meet/geetha-pardheev-chunduru/share-image"
---

# Geetha Pardheev Chunduru on Tal

## Headline

Voice AI & Distributed Systems \| Ex\-Amazon \| Ex\-Toyota Connected \| IIT Kharagpur

## About

Backend Software Engineer and IIT Kharagpur graduate with experience at Toyota Connected and Amazon building scalable distributed systems, cloud\-native services, and intelligent automation platforms\. I’ve designed large\-scale production backends in Java, Go & Rust, architected event\-driven systems and serverless workflows with AWS Lambda, DynamoDB, and SQS, and delivered impactful features including GenAI\-driven automation, voice\-controlled features for the Next\-Gen Lexus virtual assistant, and real\-time weather alerting systems\. My work bridges backend engineering, cloud infrastructure, and applied machine learning, with a focus on creating reliable, high\-performance systems that scale across platforms\.

## Location

Bengaluru

## AI stack

claude code

claude

codex

cursor

gemini

claudecode

## Work experience

Founding Engineer at hiRobin, Mar 2026 \- Present · 7 mo, Bengaluru, India, • Real\-Time AI Voice Platform: Architected and built the end\-to\-end speech\-to\-speech AI platform pow\- ering 500K\+ calls/day across 100K\+ daily active users, delivering <2s p95 conversational latency while serving 36M\+ production voice calls on multi\-region AWS infrastructure\. • Real\-Time Voice Infrastructure: Engineered voice infrastructure spanning Gemini Live and cost\-optimized ASR \+ LLM \+ TTS pipelines, implementing bidirectional audio streaming, intelligent prewarming, session migration, and resilient WebSocket recovery for production\-scale AI conversations\. • Agent Orchestration Engine: Architected and built the orchestration engine powering autonomous AI phone agents with tool\-calling, task scheduling, retries, batching, and callback recovery, executing 700K\+ outbound calls across 300K\+ autonomous task workflows\. • LLM Evaluation Infrastructure: Built the complete AI evaluation stack from scratch, including grounded regression suites, synthetic AI callers, production quality scoring, instruction\-adherence analysis, and Voice Quality dashboards evaluating 32M\+ production conversations\. • Distributed Backend Systems: Scaled core services using FastAPI, PostgreSQL, MongoDB, and Redis, eliminating distributed race conditions, optimizing cross\-region request paths, and implementing cluster\-safe coordination for real\-time workloads\. • AI Cost Optimization: Reduced Gemini Live inference costs by ∼42% through prompt redesign, input\- audio gating, canned responses, and pipeline optimization while maintaining 0\.87/1\.0 internal quality\. • Experimentation Platform: Designed and shipped an in\-house A/B experimentation framework with deterministic sticky assignment, live configuration, zero\-storage variant allocation, exposure telemetry, and production\-safe rollouts across backend services\. • Production Observability: Established core backend infrastructure with deployment pipelines, structured observability, distributed request tracing, resilient logging, and production database workflows, using call\-level correlation and PII\-masked logs to improve reliability and debugging across services\.

Software Development Engineer at Toyota Connected India, Mar 2023 \- Mar 2026 · 3 yrs 1 mo, Bengaluru, Karnataka, India, • Large Action Models: Architected and implemented a device\-agnostic backend enabling LLM inference for Generative AI–driven UI automation with function calling; delivered a 0→1 Android automation system with <6s per action \(high\-performance for UI automation\) using Amazon Bedrock & on\-device LLM reasoning\. • Scalable Automation Architecture: Built a fully containerized execution framework with Docker for re\- producible builds and efficient deployment; extending the LAM framework to integrate with Toyota One App\(Android & iOS\) and the Lexus Virtual Assistant to enable LLM\-powered UI interaction flows\. • Lexus Next\-Gen Virtual Assistant: Built high\-performance, low\-latency \(<2s\) voice features using Cap’n Proto, delivering fast and accurate interactions across HVAC, Weather, Settings, and Vehicle Info\. • Severe Weather Alerts: Designed and deployed a real\-time geo\-targeted severe weather alerts system, using AWS SQS & Redis, reducing alert\-delivery latency from 3s to <1s via smart caching\. • Smart Climate: Engineered adaptive HVAC control logic for air conditioning, fan speed, and defrosters, optimizing zone\-based microphone processing for precise, context\-aware voice recognition\.

Software Engineer at Amazon, Jun 2022 \- Mar 2023 · 10 mos, Bengaluru, Karnataka, India, Java Microservices Architecture: Architected and built backend components in Java using dependency injection \(Google Guice\) enabling regional product\-control workflows; authored and developed the auditing subsystem with AWS Lambda, DynamoDB Streams, and SQS to ensure reliable, real\-time event tracking\. Infrastructure as Code: Created, deployed and managed backend infrastructure with AWS Cloud Development Kit ensuring reproducible and CI/CD\-aligned production environments\. Operational Excellence: Implemented monitoring, alerting, and anomaly detection with AWS CloudWatch, driving proactive incident prevention and faster resolution cycles\. Resilient Event Processing: Designed and implemented retrial mechanism for extended failed event retention from 24 hours to 14 days, improving audit reliability\.

## Education

Bachelor's degree, Indian Institute of Technology, Kharagpur

[View the original profile](https://tal.club/meet/geetha-pardheev-chunduru)

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