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Metro mid-level role with a generalist title but niche voice specialization, yielding moderate competition.
Highly specialized voice realtime and ML-inference backend skills limit cross-industry transferability.
Explicit 5+ years and many mandatory low-latency, voice, and ML-serving skills imply strict filters.
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Design, build, and scale backend systems and real-time infrastructure for voice AI agents, focusing on low-latency media pipelines and high concurrency services for live conversations.
Own session and conversation-state management for thousands of concurrent live calls, ensuring context propagation and reliable handoff/escalation to human agents.
Engineer reliability into voice stack with failover, retries, load shedding, observability, and design APIs/event-driven interfaces connecting voice runtime to broader platform.
Bachelor’s degree in Computer Science or related field, or equivalent practical experience.
5+ years of experience building backend services and distributed systems with modern languages, preferably strong Python experience.
Hands-on experience with real-time, low-latency streaming media/audio systems (WebRTC, SIP, RTP) and integrating streaming ASR and TTS engines in production.
Experience serving ML/LLM models in production focused on tail latency, concurrency, and throughput; familiarity with Docker, Kubernetes, and cloud deployment (AWS/GCP/Azure).
Experienced in building and scaling real-time voice backend infrastructure from ground up with focus on low latency and reliability.
Strong systems design expertise combined with practical knowledge of streaming audio, ML inference serving, and voice platforms integration.
Capable of leading technical initiatives that integrate voice backend into existing products and collaborating with ML engineers to productionize models.