Senior Voice AI Engineer at Birdeye – Gurugram | Jobyssey

About the Role

We are looking for a Senior Voice AI Engineer to build and scale next-generation conversational Voice AI systems. You will work on real-time, low-latency voice pipelines involving Speech-to-Text (STT), Large Language Models (LLMs), Text-to-Speech (TTS), WebRTC, telephony, and streaming infrastructure.

You should have hands-on experience building production-grade Voice AI agents using frameworks like Pipecat, LiveKit, or similar real-time communication platforms. This role requires deep understanding of streaming architectures, WebSockets, voice quality optimization, interruption handling, and scalable backend systems.

About Birdeye

Birdeye is the leading agentic marketing platform for multi-location brands.

Companies like H&R Block, Aspen Dental, and Caesars Entertainment use Birdeye to manage marketing across thousands of locations — from how they get found, to how they convert, to how they retain customers. Our platform replaces disconnected point tools with AI agents that execute work at the location level — responding to reviews, updating listings, publishing content, and driving conversions.

Backed by Marc Benioff, Jerry Yang, and Accel-KKR, Birdeye was named to G2’s 2026 Best Agentic AI Products list — appearing alongside the world’s leading AI companies. We’re expanding rapidly into enterprise, with growing adoption across large, multi-location brands.

Responsibilities:

Design and build production-grade Voice AI applications.
Develop real-time streaming pipelines for voice conversations.
Integrate STT, LLM, and TTS providers into low-latency conversational systems.
Build robust WebSocket/WebRTC infrastructure for bi-directional audio streaming.
Implement interruption handling (barge-in), turn detection, and Voice Activity Detection (VAD).
Optimize latency across the complete voice pipeline.
Integrate telephony providers such as Twilio, SIP, or LiveKit Telephony.
Develop scalable backend services capable of supporting thousands of concurrent voice sessions.
Design session management, state management, and conversation memory.
Build monitoring, observability, and analytics for voice conversations.
Deploy and operate Voice AI infrastructure on Kubernetes and cloud platforms.

Required Skills:

Voice AI

Strong understanding of conversational Voice AI systems
Experience building real-time AI voice assistants
Knowledge of latency optimization techniques
Understanding of conversational memory and dialogue management

Speech Technologies

Experience with OpenAI Realtime API, ElevenLabs, Deepgram, AssemblyAI, Google Speech, Azure Speech, Amazon Transcribe, Cartesia, or PlayHT
Streaming STT and TTS
Voice cloning and adaptive speech
Speaker diarization
Custom vocabulary and pronunciation dictionaries

Real-Time Communication

Pipecat
LiveKit
WebRTC
RTP
SIP
WebSockets
Server-Sent Events (SSE)

Backend Development

Python (preferred), FastAPI, AsyncIO
WebSocket servers, gRPC, REST APIs
Event-driven architecture
Redis, Kafka, RabbitMQ
PostgreSQL, MongoDB, ClickHouse (good to have)

AI & LLM

Experience with OpenAI, Anthropic, Google Gemini, or open-source LLMs
Prompt engineering, tool calling, function calling
RAG, agentic workflows, multi-agent orchestration, conversation memory

Cloud & Infrastructure

AWS, GCP, or Azure
Docker
Kubernetes
NGINX
Load Balancers
Autoscaling
CI/CD

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