Job Description & How to Apply Below
Location:
Delhi, India (On-site)
We're hiring a Voice AI Engineer to own and scale real-time voice AI systems across STT, TTS, streaming audio, and low-latency conversational pipelines. We need someone who has built production voice systems , handled real users, and understands the engineering tradeoffs behind latency, accuracy, concurrency, and reliability.
What You'll Work On
You'll build and improve real-time voice AI pipelines involving:
STT/TTS integrations
WebRTC / Live Kit / streaming audio infrastructure
Low-latency voice agents
Hindi, Hinglish, and Indian vernacular speech workflows
Turn-taking, interruptions, barge-in, silence detection, and call handling
Production monitoring for latency, accuracy, concurrency, and reliability
What We're Looking For
2+ years of production experience in voice AI specifically
Hands-on experience with STT/TTS pipelines, WebRTC, Live Kit, or similar real-time audio infra
Experience building systems used in a real organization at scale, such as telco, consumer app, B2B SaaS, healthcare, fintech, or contact center environments
Demonstrable work with Hindi/Hinglish or other Indian vernacular voice systems is a strong plus
Ability to show quantified impact, such as:
P50/P95/P99 latency
concurrent calls/users handled
WER / accuracy improvements
call volume or user scale
uptime/reliability improvements
Strong signals
Built or owned a real-time voice agent in production
Worked with Live Kit, Twilio, WebRTC, Deepgram, Eleven Labs, Google STT/TTS, Azure Speech, or similar tools
Optimized streaming latency end-to-end
Handled noisy audio, accents, code-switching, or multilingual speech
Can debug production issues across audio, infra, LLM, STT, and TTS layers
Not a fit if
Your voice AI experience is limited to hackathons or demos
You have only built chatbot/LLM apps without real-time audio
Your resume has no quantified outcomes around latency, scale, accuracy, or reliability
Ideal profile
Someone who has already shipped voice AI to real users, knows why production audio systems break, and can independently own a low-latency voice stack from prototype to scale.
Skills:
websockets,python,voice ai
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