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Niche voice plus agentic LLM expertise and seniority reduce applicant density significantly.
Highly specialized LLM, telephony, and ASR/TTS production skills limit cross-industry transferability.
Explicit 8+ years and mandatory agentic LLM, ASR/TTS, and production-scale tech impose strict filters.
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.
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.
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.