Website:
neurodrift.ai
Job details:
NeuroDrift is a US-based AI voice and enterprise software company. We build real-time voice AI agents that run live on real phone lines, at scale, for enterprise customers. Our platform (CallDash) handles production call traffic every day — so latency, telephony quirks, and audio edge cases are our daily reality, not a research problem.
We're looking for a strong real-time voice engineer with broad expertise across the stack — someone who has shipped voice into production and debugged it when it broke under load.
What you'll do
- Build and operate real-time voice agents end to end — telephony, audio pipeline, LLM integration, tool calling
- Own latency: chase every millisecond from end-of-utterance to time-to-first-audio
- Integrate and harden SIP-trunk connections on real call platforms
- Deploy and scale stateful audio workers in production
- Take part in client meetings — present your approach and defend your technical decisions
What we need (3–4 years experience)
- 3+ years Python, including async (asyncio, FastAPI or similar)
- Real-time audio in production — WebRTC, SIP, RTP
- Production telephony integration — you've shipped at least one SIP-trunk integration on a real call platform and debugged it under load
- LLM voice integration in production — Gemini Live, OpenAI Realtime, ElevenLabs Conversational, Retell, or comparable
- Function / tool calling in voice contexts — you understand how tool-call scheduling affects perceived latency and barge-in behavior
- Kubernetes — deploying stateful audio workers with autoscaling
- A latency mindset — you instinctively reach for end-of-utterance, time-to-first-token, and time-to-first-audio metrics before the user complains
The setup
- Fully remote
- High-intensity role: 50–60 hours/week — this is startup pace, not a 9-to-5
- Working hours primarily IST, with availability for client meetings in US time zones
- You'll thrive here if you like owning hard problems end to end, you're comfortable in front of clients, and "it works on my machine" isn't in your vocabulary.
Click on Apply to know more.