Birdeye builds AI coworkers for multi-location brands. Jay for marketing, Myna for operations, and Robin for customer experience orchestrate AI agents to win AI visibility, book appointments, and drive consistent CX at every location. They run on BirdAI, the Agent OS built on 13 years of multi-location data infrastructure and 3,000+ integrations. BirdAI consolidates every signal, reasons with industry, brand and location context, and acts autonomously or with a human in the loop.

Birdeye is trusted by the world's largest multi-location brands across healthcare, dental, restaurants, financial services, auto, retail, and property management. G2 ranks Birdeye #1 in Enterprise Multi-Location Marketing Platforms and named it to the 2026 Best Agentic AI Products list. We are looking for a Senior Real-Time Voice Engineer to design, build, and optimize high-performance voice infrastructure that powers millions of automated, interactive AI voice experiences. In this role, you will own the end-to-end media pipeline—handling everything from edge routing and WebRTC streaming to real-time audio synchronization.

You will work closely with our engineering teams to ensure that real-time voice interactions across phone lines and web/mobile apps are seamless, ultra-low-latency, and highly resilient under heavy enterprise scale.

Design and implement highly concurrent, real-time backend systems that ingest, buffer, and process live audio streams with sub-second latency.

Implement core voice-handling features, including real-time speech detection, interruption handling, and streaming audio playback systems.

Manage Communications Infrastructure: Configure and scale session border controllers (SBCs), media gateways,



and WebRTC media servers to route multi-channel audio traffic reliably.

Integrate Applied AI Frameworks: Develop secure, performant integrations with industry-leading Speech-to-Text (STT) and Text-to-Speech (TTS) streaming APIs.

Establish deep observability across the voice stack to track packet health, system latency, and audio quality, ensuring a high-fidelity experience for every user.

WebRTC & Digital Media Streaming

Media Server Deployments: Hands-on experience working with open-source WebRTC media servers and SFU/MCU frameworks (e.g., Audio Optimization: Experience tuning network congestion algorithms, managing

Practical experience deploying and managing carrier-grade SBCs (e.g., Deep knowledge of SIP, RTP/RTCP, and SDP state machines, including experience writing header manipulation rules.

Experience with media duplication techniques (SIPREC / media forking) and audio codec mechanics (Opus, G.711) to normalize streaming data formats.

Packet-Level Troubleshooting: Fluency using packet analyzers like Wireshark to diagnose signaling drops, media stream anomalies, and network delays.

Modern Software & AI Infrastructure Engineering

Production Coding: Fluency in either Go (Golang) or Java for building resilient backend middleware.

Hands-on experience with WebSockets and WebRTC for real-time bi-directional data and audio streaming.

AI & Speech Models: Experience integrating streaming API endpoints with contemporary STT (Speech-to-Text) frameworks and TTS (Text-to-Speech) providers like ElevenLabs.

Engineering Best Practices: Strong background in writing clean code, designing clean SDK/API abstractions, and managing code via Git-driven CI/CD pipelines.

📌 Principal AI Platform Engineer (Gurugram)
🏢 Birdeye
📍 Gurugram