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AI Engineer - Voice & Agentic Systems

Weya AI

RemoteUnited StatesmidFull Time
Posted
today
Source
Himalayas
Field
Engineering, Data & Analytics

Skills

KubernetesOnboardingPostgreSQLPythonDockerRedisAzureAWSGCPLLMsGoAI

Description

This is a remote position. 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. Benefits Get Real Experience on "What Success looks like?" To apply:send your CV , GitHub or a demo of a voice agent you built, and one paragraph on the hardest telephony problem you've solved. Open question: application email or link. Originally posted on Himalayas

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