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:
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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