Principal Voice Platform Engineer (Conversational AI)
Birdeye
- Location
- Onsite (Gurugram, Haryana)
- Employment
- Full-time
- Level
- Senior Level
About the role
Birdeye is seeking a Principal Voice Platform Engineer to design and optimize high-performance, low-latency streaming media pipelines for conversational AI. The role involves building resilient backend infrastructure and integrating with AI speech models to power interactive voice experiences for multi-location brands.
Skills
Full job details
Role Overview
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.
What You’ll Do
- Build Streaming Media Pipelines: Design and implement highly concurrent, real-time backend systems that ingest, buffer, and process live audio streams with sub-second latency.
- Optimize Interactive Voice Systems: 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.
- Own Platform Telemetry: Establish deep observability across the voice stack to track packet health, system latency, and audio quality, ensuring a high-fidelity experience for every user.
What We’re Looking For
WebRTC & Digital Media Streaming
- WebRTC Protocol Internals: Strong understanding of the WebRTC stack, including SDP negotiation, ICE, STUN/TURN, and DTLS/SRTP security.
- Media Server Deployments: Hands-on experience working with open-source WebRTC media servers and SFU/MCU frameworks (e.g., Janus, Mediasoup, LiveKit, or Pion).
- Audio Optimization: Experience tuning network congestion algorithms, managing
- Telephony Infrastructure & Protocolsnetwork jitter buffers, and handling packet loss concealment.
- SBC & Gateway Management: Practical experience deploying and managing carrier-grade SBCs (e.g., AudioCodes, Ribbon) or open-source SIP proxies (Kamailio, OpenSIPS).
- Telephony Protocol Mastery: Deep knowledge of SIP, RTP/RTCP, and SDP state machines, including experience writing header manipulation rules.
- Media Capture & Transcoding: 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.
- Streaming Media Architectures: 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 modern 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.