Research Engineer — Agent Intelligence & Evaluation
Voice agents fail in ways traditional software doesn't. A tool call misfires when ASR confidence drops on a regional accent. An LLM hallucinates a policy because upstream latency broke turn-taking. Customer support teams roll these agents back within a week of shipping, and nobody can explain what actually went wrong.
We're building self-healing voice agents for enterprise customer support. The system has to know when it's failing, why it's failing, and how to fix itself before a human notices. This role is about building the intelligence layer behind that work: evaluations that catch failure modes before deployment, observability that traces problems across the audio, reasoning, and tool-use pipeline, and feedback loops that let agents learn from their own conversations.

What you'll work on
Three connected problems.
Evaluation frameworks for voice agents. Text-only evals miss most of what matters here (barge-in, prosody, latency-induced errors, cross-turn context loss). You'll design audio-native metrics,



generate adversarial conversational datasets across accents and edge cases, and build LLM-as-judge rubrics for task completion, empathy, and recovery from tool failures.
End-to-end observability. Tracing a failed customer interaction means correlating audio packets, STT hypotheses, LLM reasoning traces, tool calls, and TTS output back to a single conversation ID. You'll help design the schema and analysis layer that makes cascade failures visible and diagnosable across the stack.
Self-improvement systems. Once you can measure and trace, the compelling work is closing the loop: mining production traces for failure patterns, automatically generating targeted fine-tuning data or prompt updates, and validating that fixes hold under adversarial replay.

Who we're looking for
Someone who cares about the research questions for their own sake. Papers in Interspeech, ACL, NeurIPS, or EMNLP on speech, dialogue systems, a

📌 Founding Research Engineer (New Delhi)
🏢 ixigo
📍 New Delhi