Who are we?

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 delivers industry-specific solutions powered by AI, tailored workflows, and seamless automation.

Kapture CX is headquartered in Bangalore and we have offices in Mumbai and Delhi/NCR in India, in addition to offices in the USA, UAE, Singapore, Philippines and Indonesia.

What is this role all about?

As an AI Delivery Intern, you will support the end-to-end delivery of AI voicebots and chatbots for enterprise clients. You will work directly alongside the AI Delivery team on prompt engineering, conversation design, and the speech and language pipeline (STT → LLM → TTS) that powers our bots — turning client requirements into live, production-grade conversational experiences.

Sounds interesting?

Here's a more detailed description of what you will do in this role:

• Write, test, and iterate prompts for LLM-powered voicebots and chatbots — designing conversation flows, tool-calling logic, and guardrails for real client use cases.
• Design and refine conversation experiences across multi-turn, multi-intent, and multilingual scenarios.
• Configure and tune the speech pipeline — evaluating and optimizing Speech-to-Text (STT), Text-to-Speech (TTS), and LLM components for accuracy, latency, and naturalness.
• Perform log-based root cause analysis — inspecting conversation logs, tracing errors, and identifying why a bot behaved unexpectedly, then proposing fixes.
• Build and run QA / evaluation frameworks to measure and improve conversation quality against defined parameters.
• Support client rollouts — preparing test cases, validating flows before go-live, and helping resolve issues during and after launch.
• Document configurations, findings, and best practices to help the team scale delivery across accounts.

This is a Bangalore based role. We work five days a week from the office, as we believe in-person interactions fuel innovation and agility.

What does success look like in this role?

• You take ownership and think proactively about getting a bot to work reliably in production.
• You have a strong debugging mindset — inspecting logs, tracing errors, and finding root causes quickly.
• You can pick up new tools, stacks, and monitoring systems (e.g. log analytics, dashboards) with minimal hand-holding.
• You communicate technical findings clearly to both technical and non-technical stakeholders.

What would make you a good fit for this role?

Here are the basic requirements:

• An engineering background (or equivalent hands-on technical grounding) — comfortable reading code, working with APIs, and understanding data flows.
• Working knowledge of Python and comfort with JSON, REST APIs, and system integrations.
• Exposure to prompt engineering and Large Language Models (GPT, Claude, Gemini, or similar) — you’ve experimented with prompting and understand how LLMs behave.
• A basic understanding of speech technologies — STT (ASR) and TTS — and what affects their quality.
• Familiarity with chatbots / voicebots or conversational AI, even at a project or hobby level.
• Strong problem-solving and debugging instincts, and clear written communication.
• Eagerness to learn fast in a dynamic, client-facing delivery environment.

What are the most critical skills for this role?

• You take ownership and think proactively about getting a bot to work reliably in production.
• You have a strong debugging mindset — inspecting logs, tracing errors, and finding root causes quickly.
• You can pick up new tools, stacks, and monitoring systems (e.g. log analytics, dashboards) with minimal hand-holding.
• You communicate technical findings clearly to both technical and non-technical stakeholders.

You will have an advantage if you:

• Have built anything with LLM APIs, prompt frameworks, or agentic / tool-calling setups.
• Have exposure to telephony or voice platforms, or to multilingual / Indian-language NLP.
• Have worked on QA, evaluation, or automated testing of AI systems.

Why should you be interested?

Here's what you will gain from this role:

• Hands-on ownership of live, large-scale conversational AI deployments for top enterprise brands.
• Deep, practical exposure to the full voice AI stack — prompt engineering, STT, LLMs, and TTS.
• Mentorship from an experienced AI delivery team, working independently with real client impact.
• A strong launchpad into product, AI delivery, and applied ML roles in a fast-scaling global SaaS company.

Does this sound like you?

Click the Apply button to let us know!