Lead AI Engineer – Agentic Systems & Voice AI

Role Overview We are seeking a highly experienced Lead AI Engineer to architect, deploy, and scale intelligent, agentic voice systems capable of handling massive production traffic. This role focuses on building ultra-low-latency, full-duplex conversational voice agents using cascaded architectures (ASR -> LLM -> TTS) tailored for Indian languages. You will act as the technical bridge between complex client workflows and scalable AI capabilities, ensuring robust backend execution, optimal resource efficiency, and seamless human-computer interaction at enterprise scale. Core Responsibilities Full-Duplex Voice Architecture: Design and orchestrate conversational AI pipelines without relying on native multimodal/full-duplex LLMs. Build and tune highly responsive turn-taking logic, Voice Activity Detection (VAD), and barge-in/interruption handling across cascaded ASR, LLM, and TTS components. Telephony & API Integration: Seamlessly bridge AI inference pipelines with standard telephony APIs (Twilio, Plivo, Exotel) for inbound and outbound agent call flows, managing basic call state (transfers, hold, drop detection). Agentic Workflow Orchestration: Collaborate directly with clients to deconstruct complex business requirements and operational workflows. Translate these into deterministic agentic capabilities, utilizing state machines, tool-calling, and external API integrations to execute multi-step reasoning tasks. Latency & Efficiency Optimization: Drive hardcore performance tuning across the entire stack. Optimize Time-To-First-Token (TTFT), Time-To-First-Audio (TTFA), and Real-Time Factor (RTF) over phone lines. Implement model quantization, KV cache optimization, dynamic batching, and efficient model serving to minimize latency under heavy concurrent loads. Indic Language Mastery: Lead the development of multilingual systems that natively handle the phonetic and linguistic nuances of Indian languages. Solve complex challenges related to code-switching (e.g., Hindi-English, Telugu-English), regional accents, and low-resource language modeling. Backend & Production Scale: Architect resilient, event-driven backend systems capable of sustaining high-throughput production traffic. Manage stateful asynchronous processes, distributed microservices, and robust data pipelines to ensure zero-downtime deployments and real-time observability. Required Qualifications & Experience Experience Baseline: 8+ years of overall software engineering and AI/ML experience, with a strict minimum of 3+ years directly architecting and deploying agentic LLM systems and complex conversational AI in production. Production System Expertise: Deep understanding of backend engineering for high-concurrency environments. Proven experience with distributed systems, event-driven architectures (e.g., Apache Kafka), workflow orchestrators (e.g., Temporal), and high-performance databases (e.g., PostgreSQL, ClickHouse). Conversational AI Depth: Strong operational knowledge of…