AI Engineer - Voice & Agentic Systems

Weya.ai; United States; Remote; USD 13,000 - 19,000; Full time

Job summary

Weya.ai is seeking an AI Engineer to design, build and run voice-enabled agents for client conversations. You will work on LLM orchestration with LlamaIndex and LangChain, develop FastAPI services behind agents, and implement real-time voice pipelines with STT/TTS and telephony integrations.

You\'ll own an agent end to end, from prompt to concurrent calls, and collaborate with customers to turn transcripts into better agent experiences.

Qualifications

• Shipped production agents using LlamaIndex and/or LangChain with tool use, memory and RAG.
• Extensive experience building async Python services with FastAPI, Pydantic, WebSockets and background workers.
• Hands-on work on STT/TTS providers and latency tuning for live voice agents.
• Experience integrating multiple telephony providers and SIP setups.

Responsibilities

• Design, build and run agents that talk to customers via real-time voice pipelines.
• Develop FastAPI services behind agents with async endpoints and WebSockets.
• Implement low-latency voice agent workflows including STT/TTS and voice activity handling.
• Integrate telephony providers (Twilio, Exotel, Vonage, SIP) with code and maintain audio flows.
• Engineer for failures with retries, timeouts, and idempotent calls to ensure campaign reliability.
• Write unit and integration tests and build regression suites for agent behavior.
• Instrument metrics like latency per turn, call success rates, and cost per call.

Skills

LlamaIndex

LangChain

FastAPI

Python

WebSockets

Pydantic

Async services

Tools

Twilio

Exotel

Vonage

Docker

Kubernetes

Redis

Postgres

Kafka

Job description

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 AI 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.