Role Name:

At Kapture CX, we are looking for an AI Delivery Intern in our tech team.

Who are we?

What is this role all about?

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.

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?