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Niche voice-AI expertise but mid-level seniority and Bangalore location increase candidate competition.
High domain specificity; real-time voice AI production skills transfer poorly across industries.
Multiple mandatory filters: 5+ years, 2+ years voice-in-production, and performance Go experience.
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Own and operate distributed, real-time voice AI systems that manage thousands of simultaneous calls with high reliability and low latency.
Ensure end-to-end conversational latency remains under ~800ms by managing components like STT/ASR, LLM, TTS, RAG, tool-calling, and network hops.
Diagnose issues in the voice pipeline rapidly, build measurable voice quality evaluations, and make provider trade-offs to optimize quality and latency.
Minimum 5 years of professional experience with production systems, including at least 2 years specifically in real-time voice AI in production environments.
Strong proficiency in Go and Python, with experience rewriting performance-critical components in Go to improve throughput under load.
Deep understanding of the full voice AI pipeline and experience operating high concurrency voice AI platforms (like Pipecat) at scale.
Location requirement: Bangalore office. Notice period: Not explicitly mentioned in the JD.
Experienced engineer specialized in scaling and maintaining real-time voice AI pipelines with proven operational excellence under enterprise loads.
Practitioner with hands-on expertise in balancing provider trade-offs across STT, LLM, TTS, and related components to optimize voice quality and latency.
Data-driven mindset with a track record of building and running voice quality evaluation systems that inform release gating and mitigate provider drift.