AI Engineer - Voice & Agentic Systems

Weya AI; Dadri; Híbrido; INR 1.800.000 - 2.800.000; Jornada completa

Descripción de la vacante

Weya AI is hiring an AI Engineer (Voice & Agentic Systems) to design, build, and run the end-to-end agents that interact with clients' customers. You will work on LLM orchestration, real-time services, and voice pipelines integrated with multiple telephony providers, delivering reliable, scalable solutions across India and beyond.

You will own agents end to end from prompt to production, tackling concurrency, latency, and edge-case handling while collaborating with customers and frontline

Formación

• Shipped production agents with LlamaIndex and/or LangChain
• Extensive experience building async Python services with FastAPI, Pydantic, WebSockets
• Voice agents that handled real customer calls with STT/TTS providers and latency tuning
• Telephony: integrated two or more providers or SIP setups and explained audio flow

Responsabilidades

• Build agentic workflows with LlamaIndex and LangChain: tool calling, RAG over policy and loan documents, multi-step reasoning, and guardrails for regulated conversations
• Design and run FastAPI services that serve agents in real time: async endpoints, WebSockets, webhooks, background tasks and clean API contracts
• Build low-latency voice agents end to end: STT, LLM, TTS, voice activity detection, barge-in/interruption handling, and turn-taking
• Integrate and maintain telephony providers (e.g. Twilio, Plivo, Exotel, Vonage, SIP trunks): inbound/outbound calls, call transfer, recordings, DTMF, and media streaming
• Engineer for failure: provider outages, dropped calls, LLM timeouts, partial transcripts, retries and idempotency
• Write tests that catch problems before clients do: unit and integration tests, simulated calls, load tests, and regression suites for agent behaviour
• Instrument everything: latency per turn, call success rates, cost per call, and alerts that fire before a client notices
• Work directly with FDEs and clients to turn real call transcripts into better agents

Conocimientos

LangChain

LlamaIndex

Real-time systems

Telephony integration

Debugging under pressure

API orchestration

Herramientas

FastAPI

Pydantic

WebSockets

Twilio

SIP trunks

Descripción del empleo

Job Title: AI Engineer (Voice & Agentic Systems)

Location: Noida

Working Mode: Remote

Type: Full-time

Experience: 2+ Years (shipping LLM agents)

About the Company

weya builds AI automations - Voice, video and WhatsApp agents that banks, lenders and insurers put in front of their customers. Our agents handle collections, onboarding, renewals, KYC follow-ups and support calls at scale, across India, the Middle East & Africa, Australia and the US. We're a small team of 11-15 people. Every engineer ships to production, talks to customers, and owns real outcomes. If an agent mishandles a loan call, it costs a client money and trust, so we build for reliability first.

About the Role

You'll design, build and run the agents that talk to our clients' customers: LLM orchestration with LlamaIndex/LangChain, FastAPI services behind them, and real-time voice pipelines wired into telephony providers. You own an agent end to end, from the first prompt to the 10,000th concurrent call.

What You'll Do?

• Build agentic workflows with LlamaIndex and LangChain: tool calling, RAG over policy and loan documents, multi-step reasoning, and guardrails for regulated conversations.
• Design and run FastAPI services that serve agents in real time: async endpoints, WebSockets, webhooks, background tasks and clean API contracts.
• Build low-latency voice agents end to end: STT, LLM, TTS, voice activity detection, barge-in/interruption handling, and turn-taking.
• Integrate and maintain telephony providers (e.g. Twilio, Plivo, Exotel, Vonage, SIP trunks): inbound/outbound calls, call transfer, recordings, DTMF, and media streaming.
• Engineer for failure: provider outages, dropped calls, LLM timeouts, partial transcripts, retries and idempotency, so one bad dependency never takes down a campaign.
• Write tests that catch problems before clients do: unit and integration tests, simulated calls, load tests, and regression suites for agent behaviour.
• Instrument everything: latency per turn, call success rates, cost per call, and alerts that fire before a client notices.
• Work directly with FDEs and clients to turn real call transcripts into better agents.

Requirements

What We're Looking For? (Non-Negotiable)

• Agentic frameworks: shipped production agents with LlamaIndex and/or LangChain (or LangGraph), including tool use, memory and RAG. Not just notebooks.
• FastAPI: extensive experience building async Python services with FastAPI, Pydantic, WebSockets and background workers, under real traffic.
• Voice agents: built at least one voice agent that handled real customer calls, with hands-on work on STT/TTS providers (e.g. Deepgram, ElevenLabs, Azure, Google) and latency tuning.
• Telephony: integrated two or more telephony providers or SIP setups, and can explain how audio flows from a phone network to your code and back.
• Production mindset: you think about concurrency, rate limits, timeouts, retries and edge cases before writing the happy path, and you write tests for them.
• Debugging under pressure: comfortable reading logs, call recordings and traces to find why a call failed.
• Clear written English; able to explain a technical trade-off to a client.

Good to have (Bonus Points)

• Real-time voice frameworks such as LiveKit Agents or Vapi, or speech-to-speech models.
• Go for high-throughput services alongside Python.
• Multilingual voice work, especially Hindi, Hinglish, Arabic or other Indic languages.
• Experience in BFSI or other regulated domains: consent, call recording rules, PII handling, audit trails.
• LLM evaluation: automated scoring of agent conversations, prompt regression testing.
• WhatsApp Business API or video agent experience.
• Docker, Kubernetes, AWS/GCP, Redis, Postgres, and queues like Kafka or RabbitMQ.

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