Platform: Convogent

Level: Mid–Senior (5+ years | 2+ years building voice AI in production)

Location: Bangalore Office

About The Role

You will own the distributed, real-time systems that orchestrate parallel voice calls at massive scale: the core platform behind every conversation Convogent runs. The job is keeping thousands of simultaneous calls fast, reliable, and natural, owning how STT/ASR, LLM, TTS, RAG, and tool-calling work together, and where every millisecond and every point of quality goes across the pipeline.

What You’ll Do

Own voice AI at scale. Keep the pipeline rapid and reliable at enterprise concurrency, thousands of simultaneous calls, by lifting calls-per-vCPU through extending Pipecat or rewriting hot paths in Go.
Own end-to-end latency. Keep the conversation under ~800ms by decomposing the budget across STT, LLM, TTS, RAG, tool-calling, turn-detection, and network hops.
Diagnose the bad call. When a call does not feel right, locate the fault in the pipeline rapid by asking the right questions, reading the right signals, and owning the fix.




Make quality measurable. Build voice-to-voice evals that gate releases and catch STT/LLM/TTS provider drift before customers do.
Own provider tradeoffs. Decide how STT / LLM / TTS / RAG / tool-calling choices balance voice quality against latency, per conversation flow.
Build adjacent products. Extend the platform into live assist, agent assist, and what comes next, on the same pipeline foundations.
Set the bar. Review, mentor, and define engineering standards for a growing team.

What We’re Looking For

5+ years building production products and systems, with at least 2 of those years in real-time voice, operating it in production, not just shipping a demo.
Deep understanding of the full voice pipeline, every stage end to end and how each one affects the next and shapes quality and latency.
Solid in Go/Python, comfortable across the whole pipeline. Production-grade, performance-critical Go is especially va

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