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Recognizable startup, metro location, mid-level title but niche voice/real-time specialization reduces competition.
Highly specialized voice, real-time streaming and ML inference skills limit industry transferability.
Mandatory 5+ years plus specialized voice, streaming, ML inference, and cloud/Kubernetes skills enforce high filtering.
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Design, build, and scale low-latency, real-time voice backend systems including audio streaming pipelines and orchestration layers for AI voice agents.
Own session and conversation-state management for thousands of concurrent live calls ensuring context propagation and seamless escalation to human agents.
Build and operate highly scalable backend services to serve ML/LLM speech and language models optimizing for tail latency, concurrency, and cost.
Bachelor's degree in Computer Science or related field, or equivalent practical experience.
5+ years experience building backend services and distributed systems using languages like Python, Golang, or Java.
Hands-on experience with real-time, low-latency streaming media or audio systems (e.g. WebRTC, SIP, RTP) and integration/operation of streaming ASR and TTS engines in production.
Experience serving ML/LLM models in production with focus on latency, concurrency, and throughput; familiarity with REST API design and event-driven architectures.
Proven expertise in distributed backend system design for real-time, multi-turn voice AI applications with a focus on latency and reliability.
Operational experience running and scaling streaming audio, ASR, and TTS services integrated with AI models under strict performance SLAs.
Strong technical leadership in integrating voice backend systems with broader platform components and ML engineering teams.