At Kapture CX, we are looking for a Technical Product Manager – Applied AI (Voice) to drive continuous improvement of our Voice AI platform through hands-on experimentation, real-world testing and deep system understanding.
Kapture CX is a leading SaaS platform that helps enterprises automate and elevate customer experience through intelligent, AI-powered solutions. We partner with enterprises across industries to bring scalable automation and insight-driven efficiencies to their CX operations. Over a thousand clients across 18 countries have used Kapture’s products to enhance their customer experience, including Unilever, Reliance, Coca-Cola, Bigbasket, Meesho, Airtel Payments Bank and Cathay Pacific.
Kapture CX is headquartered in Bangalore, with offices across India, the USA, UAE, Singapore, Philippines, and Indonesia.
This is a hands-on, high-impact role focused on improving the real-world performance of our Voice AI platform.
You will work at the intersection of LLMs, voice systems, and product behavior — testing new models, experimenting with prompting strategies, evaluating configurations and identifying what actually works in production.
You will not just support implementations - you will shape how the product evolves by feeding structured insights from experimentation, debugging and real-world usage back into the product roadmap.
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Test and benchmark different LLMs, STT/TTS systems and configurations across use cases
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Evaluate performance across latency, accuracy, cost and conversation quality
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Run structured experiments to compare prompts, multi-agent setups and orchestration strategies
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Design and refine prompts, guardrails, fallback strategies and conversation flows
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Improve handling of noisy ASR, multilingual inputs and edge-case scenarios
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Continuously optimize conversation quality based on real call data
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Analyze logs, traces and transcripts to identify failure points
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Distinguish between model issues, prompt gaps, platform limitations and integration problems
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Propose and validate fixes through rapid iteration
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Identify recurring gaps and translate them into clear product requirements
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Work closely with Product and Engineering teams to prioritize improvements
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Act as the voice of “what works in production” for the product roadmap
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Develop practical workarounds for current system limitations
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Balance ideal AI behavior with real-world constraints (latency, APIs, data availability)
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Improve system reliability and robustness across deployments
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Measurable improvement in voicebot accuracy, latency, and conversation quality
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Faster identification and resolution of system issues
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Clear, actionable inputs into product and model decisions
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Better adoption of new models and architectures (e.g., multi-agent setups)
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Strong alignment between real-world performance and product capabilities
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4+ years of overall experience with atleast 2+ years in AI products, voicebots, conversational AI or applied ML roles
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Strong hands-on experience with prompt design, experimentation, and debugging
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Deep understanding of voice AI systems (ASR, TTS, latency, turn-taking, interruptions etc.)
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Ability to evaluate models and configurations pragmatically (not just theoretically)
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Comfort working with logs, system behavior, and ambiguous real-world issues
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High ownership and bias for action
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Have prior experience working on voicebot platforms or conversational AI systems
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Have experimented with multiple LLMs and orchestration approaches
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Have worked in delivery or implementation roles and understand real-world constraints
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Work on cutting-edge applied AI problems with direct production impact
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Influence both product direction and real-world system behavior
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Get hands-on exposure to evolving LLM and voice AI ecosystems
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Play a key role in shaping how AI systems perform at scale
Does this sound like you?
Click the Apply button to let us know!
