We're helping an AI startup based out of Delhi founded by IIT and IIM Alumni hire a Voice AI Engineer.
About the Role
We are looking for a Voice AI Engineer to build and improve real-time voice agents that can handle natural, reliable, human-like conversations over phone calls. You will work across speech, LLMs, telephony, backend systems, and agent orchestration to build production-grade AI calling experiences.
This role is ideal for someone who has hands-on experience building voice agents, understands the latency and reliability challenges of real-time audio, and can own systems end-to-end from prototype to production.
Responsibilities
- Build and maintain real-time Voice AI agents for inbound and outbound calls.
- Work with speech-to-text, text-to-speech, LLMs, and voice orchestration pipelines.
- Integrate with telephony platforms such as Twilio, Plivo, Exotel, Vonage, or similar.
- Design low-latency conversation flows with interruption handling, turn-taking, retries, fallbacks, and human handoff.
- Improve agent quality across:
- Latency
- Accuracy
- Naturalness
- Conversation completion rate
- User satisfaction
- Build backend services for call handling, logging, analytics, and agent state management.
- Integrate voice agents with CRMs, EMRs, scheduling tools, internal dashboards, databases, and APIs.
- Create evaluation frameworks for voice agent performance, including call success rate, hallucination rate, escalation rate, and transcription quality.
- Debug production issues related to audio streams, WebSockets, telephony failures, latency spikes, and LLM behavior.
- Collaborate with product, design, and operations teams to ship reliable voice experiences for real users.
Requirements
- 1+ years of hands-on engineering experience.
- Experience building Voice AI agents, conversational AI systems, or real-time audio applications.
- Strong backend engineering skills in Python, Node.js, TypeScript, or Go.
- Experience working with LLM APIs such as OpenAI, Anthropic, Gemini, or open-source models.
- Familiarity with speech-to-text and text-to-speech systems such as Deepgram, AssemblyAI, Whisper, ElevenLabs, Cartesia, PlayHT, Azure Speech, Google Speech, or similar.
- Experience with WebSockets, streaming APIs, async processing, and event-driven systems.
- Understanding of real-time voice challenges such as:
- Latency optimization
- Barge-in / interruption handling
- Silence detection
- Voice activity detection
- Turn detection
- Audio quality issues
- Call drops and retries
- Ability to write clean, reliable, production-ready code.
- Strong debugging skills and comfort working with ambiguous problems.
Good to Have
- Experience with Twilio Media Streams, SIP, IVR systems, call routing, or PSTN infrastructure.
- Experience building voice agents using frameworks such as LiveKit Agents, Vapi, Retell, Bland, Pipecat, Daily, or similar.
- Experience with RAG, tool calling, agentic workflows, and structured outputs.
- Experience with healthcare, fintech, logistics, customer support, sales, or operations voice workflows.
- Experience building dashboards for call review, QA, analytics, and human-in-the-loop correction.
- Knowledge of prompt engineering, conversation design, and LLM evaluation.
- Experience deploying systems on AWS, GCP, Azure, Railway, Render, or similar.
- Familiarity with compliance-sensitive environments such as HIPAA, SOC 2, or GDPR is a plus.
What You'll Work On
- AI agents that can make and receive phone calls.
- Real-time conversation systems with low latency.
- Voice workflows for scheduling, reminders, support, qualification, follow-ups, and data collection.
- Integrations with internal tools and third-party platforms.
- Evaluation systems to continuously improve agent reliability.
- Infrastructure that can scale from demos to production usage.
Ideal Candidate
You are someone who has actually built voice agents or real-time conversational systems, not just chatbots. You understand that voice AI is different from text AI because users expect fast responses, smooth turn-taking, natural speech, and high reliability.
You are comfortable working across the full stack: audio streaming, LLMs, backend APIs, telephony, databases, and deployment. You enjoy debugging hard production issues and improving systems through fast iteration.
