Lead AI Engineer – Agentic Systems & Voice AI
YAL.ai (company site, opens in a new tab)8+ yrsHyderabadOn-siteDirect career pageEst. 30–55 LPA
Posted on 18 Sept
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Job description
Structured overview of role & requirements
About This Role
- Architect and scale real-time conversational voice AI systems using cascaded ASR -> LLM -> TTS pipelines tailored for Indian languages, focusing on ultra-low latency and high concurrency.
- Integrate conversational AI with telephony APIs (Twilio, Plivo, Exotel) to manage agent call workflows including transfers, hold, and drop detection.
- Collaborate with clients to translate complex business workflows into deterministic AI agent capabilities using state machines and API integrations with robust backend for large-scale production deployment.
Minimum Requirements
- 8+ years in software engineering and AI/ML with minimum 3+ years architecting and deploying agentic LLM-based conversational AI in production.
- Strong expertise in backend systems for high-concurrency, including distributed event-driven architectures (e.g., Apache Kafka), workflow orchestration (e.g., Temporal), and high-performance databases (PostgreSQL, ClickHouse).
- Operational knowledge of speech processing models (ASR/TTS), streaming protocols (WebRTC, gRPC, WebSockets), and handling real-time voice interaction state management.
- Experience with high-performance model serving and optimization (vLLM, NVIDIA Triton, TensorRT) and integrating telephony APIs for voice call management.
Ideal Candidate Profile
- Technical architect comfortable translating complex, domain-specific business processes (e.g., CRM automation, public grievance handling) into scalable AI agent workflows.
- Experience leading development of multilingual voice systems addressing Indian language nuances including code-switching and regional accents.
- Proficient in full-stack conversational AI delivery including backend microservices, latency optimization, telephony integration, and real-time observability at enterprise scale.