AI Engineer – Voice Agents

We are looking for an experienced AI Engineer (Voice Agents) who has designed, built, and deployed production-grade AI voice agents not just prototypes. You'll join a fast-moving, product-led team where ideas go from MVP to production in weeks, not quarters.

This is a hands-on role for someone who enjoys owning the full lifecycle architecture, modeling, evaluation, deployment, monitoring, and iteration.

What You'll Do

1. Build & Ship Voice Agents

• Design, build, and deploy inbound and outbound voice agents for real-world business workflows.
• Own E2E pipeline — speech-to-text, LLM reasoning, prompt strategy, dialog state management, TTS, telephony integration.
• Rapidly iterate MVPs and harden them to production quality with robust SLAs.

2. Engineering & Architecture

• Architect scalable agentic systems using modern tooling (OpenAI, Anthropic, DeepSeek, Inspector, Whisper, PlayHT, ElevenLabs, PolyAI-style dialog).
• Implement retrieval (RAG), vector stores, and memory systems to boost accuracy in complex tasks.
• Integrate voice agents with CRM, ticketing, telephony, and workflow orchestration systems.

3. Production & Reliability

• Set up observability: monitoring, logging, red-teaming, evals, hallucination detection.
• Drive latency reduction, call-success metrics, correctness of agent actions.
• Run A/B tests, fine-tuning, guardrails, fallback flows.

4. Collaboration & Product Work

• Work closely with product, engineering, and domain stakeholders to define agent behavior.
• Translate business processes into voice agent flows that operate with high autonomy.
• Contribute to internal frameworks and reusable components for deploying voice agents faster.

What You Bring

• 4–7 years of hands-on AI/ML engineering experience.
• At least one real, production-deployed AI voice agent (inbound or outbound) that handled real customer calls.
• Deep expertise in:
• Speech-to-Text (Whisper, AssemblyAI, Deepgram, Google STT)
• LLMs (OpenAI, Anthropic, Llama, Gemini, DeepSeek)
• Text-to-Speech (ElevenLabs, PlayHT, Azure TTS)
• Telephony (Twilio, SIP, WebRTC, Asterisk, etc.)
• RAG, embeddings, vector databases
• Python/Node JS for AI agent orchestration
• Experience deploying production microservices (Docker, Kubernetes, CI/CD).
• Strong latency optimization + debugging skills — especially for real-time audio.
• Ability to work in fast environments: MVP in weeks → robust production in months.

Nice to Have

• Experience with vendor ecosystems like ElevenLabs, PolyAI, Sierra, Decagon, Replicant.
• Experience building frameworks for agent evaluation and "reasoning trace" inspection.
• Background in conversation design or dialog management.
• Experience with reinforcement learning for dialog optimization.

Success Looks Like

• In the first 2–4 months you will:
• Deliver at least one production-ready voice agent handling real customer traffic.
• Build internal tooling that reduces time to deploy new agents.
• Improve latency, call success rate, and downstream business outcomes.
• Establish metrics, dashboards, and evaluation tooling for all voice agents.
• Become the go-to owner for AI voice agent architecture and innovation.

_ Why Join Us_

• Work directly with experienced founders and a high-caliber product/engineering team.
• Own end-to-end systems with massive autonomy.
• Ship real products that touch thousands of customers.
• Opportunity to shape core AI infrastructure and voice agent strategy.
• Competitive compensation + high-growth environment.

How to Apply

Send your GitHub/portfolio, past projects, and a brief note on the voice agents you've deployed to:

Required: Please create your profile on )

Job Type: Full-time

Pay: ₹2,200, ₹3,500,000.00 per year

Benefits:

• Work from home