Live opening · Posted 1 day ago

Backend Engineering Intern, Voice AI Platform

Zudu AI · Chennai, Tamil Nadu, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 1 day ago
CompanyZudu AI
LocationChennai, Tamil Nadu, India (On-site)
Work modeNo
SourceLinkedin
Listed1 day ago

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About the role

Description supplied by the original job listing.

About Zudu AI
Zudu AI is an enterprise Voice AI platform. Our real-time AI voice agents handle live customer calls in production for enterprise customers in India and overseas. The stack: Python (FastAPI) and Java (Spring Boot) services, LiveKit for real-time media, SIP telephony, STT/TTS, LLMs, PostgreSQL, Qdrant, and Kubernetes on GCP.
The role
This is not a training programme. You will ship to production within your first month, own small services end to end, and debug live call flows with the core team. We build with AI tooling (Claude Code, Cursor) every day and expect you to.
What you'll do
Build and maintain backend services and APIs in Python/FastAPI (primary) and Java/Spring Boot
Build and support real-time voice agent workflows on LiveKit, including SIP/telephony integration and call control
Integrate LLMs, speech (STT/TTS) and RAG (PostgreSQL + Qdrant) into production agents
Debug across APIs, WebSocket and SIP flows, and Kubernetes workloads on GCP using logs, metrics and traces
Ship tested, reviewed code through CI/CD
The bar (read before applying)
Final-year student or 2025/2026 graduate in CS, IT or a related field
At least one real backend project outside coursework (internship, freelance or personal): deployed, used by someone other than you, code on GitHub
You have built something with an LLM API (RAG, embeddings, agents or tool calling) and can explain where it failed
You use AI coding tools daily and know where their output needs fixing
Solid fundamentals: HTTP/REST, SQL, async or concurrency basics, Git
You can read a stack trace and logs and form a hypothesis before asking for help
Comfortable in Python or Java, willing to work in both
Nice to have
FastAPI, Spring Boot, WebSockets, asyncio
SIP, VoIP, WebRTC or LiveKit
Docker, Kubernetes, GCP
Open source contributions
What you'll gain
Production experience on a real-time Voice AI platform (telephony, media pipelines, LLM integration, cloud-native infra), direct mentorship from the core engineering team, and a full-time path for strong performers.

Work arrangement
No

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