Kapture CX is Hiring AI Delivery Intern (Voicebot & Conversational AI) | Bangalore | Freshers

Job Description

This is one of the more genuinely rare fresher-level AI internships worth flagging specifically: most "AI internship" listings in India are either vague data-labeling work or generic "exposure to ML" roles, but Kapture CX's opening puts interns directly on production voicebot delivery for enterprise clients like Unilever, Coca-Cola, and Meesho — meaning your work could plausibly be live in a real customer-facing bot, not a sandboxed practice project. For engineering students specifically interested in applied LLM work rather than pure research, this is a notably hands-on entry point.

The role centers on the 𝐟𝐮𝐥𝐥 𝐜𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞 — prompt engineering and conversation design on one end, speech technology (STT/TTS) tuning on the other, tied together by log-based debugging when bots misbehave in production. Realistically, the steepest learning curve for most CS/engineering freshers won't be the LLM/prompting side (which is increasingly covered in coursework and widely self-taught via ChatGPT/Claude experimentation) but the 𝐬𝐩𝐞𝐞𝐜𝐡 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐚𝐧𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐝𝐞𝐛𝐮𝐠𝐠𝐢𝐧𝐠 𝐬𝐢𝐝𝐞 — evaluating STT/TTS accuracy and tracing why a live bot failed requires a different, less commonly taught skill set than general programming.

𝐒𝐤𝐢𝐥𝐥𝐬-𝐰𝐢𝐬𝐞, the listing is unusually specific about what "exposure" actually means: not formal certification, but genuine hands-on experimentation — the posting explicitly wants candidates who've personally prompted LLMs like GPT, Claude, or Gemini and understand their behavior, even at hobby-project level. This is a skill combination that's become more accessible over the past year (given how widely available LLM APIs now are), but pairing it with actual debugging/root-cause-analysis instincts and basic speech-tech understanding remains uncommon among fresh graduates — most self-taught LLM experimenters stop at prompting and don't touch STT/TTS or production log analysis at all.

𝐎𝐮𝐫 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬:

𝐆𝐎𝐎𝐃 𝐅𝐎𝐑: Engineering students who've genuinely built something with LLM APIs (even a small personal project) and want real production exposure rather than theoretical AI coursework.

𝐍𝐎𝐓 𝐈𝐃𝐄𝐀𝐋 𝐅𝐎𝐑: Those without any hands-on API/coding comfort — this isn't a "learn AI from scratch" internship; it assumes working Python and REST API fluency already.

𝐒𝐄𝐋𝐄𝐂𝐓𝐈𝐎𝐍 𝐃𝐈𝐅𝐅𝐈𝐂𝐔𝐋𝐓𝐘: Likely high relative to typical fresher internships — the combination of LLM experimentation + speech tech awareness + debugging instinct is a narrow, specific profile, so a demonstrable personal project matters more here than GPA.

𝐂𝐀𝐑𝐄𝐄𝐑 𝐓𝐑𝐀𝐉𝐄𝐂𝐓𝐎𝐑𝐘: Positions well for AI Delivery, Applied ML, Conversational AI Engineer, or Product/AI roles at SaaS companies — genuinely rare production-scale exposure this early in a career.

𝐂𝐨𝐦𝐩𝐞𝐧𝐬𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: Kapture CX hasn't disclosed a stipend for this role. AI/ML-focused internships at Bangalore SaaS companies generally range from ₹15,000–₹30,000/month depending on company scale and candidate strength — this is a general estimate, not confirmed, and could vary given how specialized this particular role is.

𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐲: Since the listing explicitly values hands-on LLM experimentation over formal credentials, lead your application with a specific example — even a small personal chatbot, a prompt-engineering experiment, or a GitHub repo using an LLM API — rather than listing "AI/ML" as a general interest area; given how specific the requirements are (STT/TTS awareness, debugging mindset), generic AI enthusiasm without a concrete project is unlikely to stand out here.

Roles & Responsibilities

The role splits into three connected areas: 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 (writing and iterating prompts, designing conversation flows), 𝐭𝐮𝐧𝐢𝐧𝐠 (optimizing the STT→LLM→TTS pipeline for accuracy and latency), and 𝐦𝐚𝐢𝐧𝐭𝐚𝐢𝐧𝐢𝐧𝐠 (debugging production issues via log analysis and supporting client go-lives) — meaning you're involved across the entire lifecycle of a voicebot, not just one narrow piece of it.

- Write, test, and iterate LLM prompts for voicebots/chatbots, including tool-calling logic and guardrails.

- Configure and tune the speech pipeline (STT, TTS, LLM components) for accuracy and naturalness.

- Perform root cause analysis on conversation logs to diagnose unexpected bot behavior.

- Build QA/evaluation frameworks to measure and improve conversation quality.

- Support client rollouts — test case preparation, pre-launch validation, and post-launch issue resolution.

- Document configurations and best practices to help the team scale delivery.

Qualifications & Eligibility

The eligibility bar leans on demonstrated hands-on ability rather than formal degree specifics — an engineering background is expected, but the real qualifying factor is genuine prior experimentation with LLMs and APIs.

- Engineering background or equivalent hands-on technical grounding.

- Working knowledge of Python, JSON, REST APIs, and system integrations.

- Prior hands-on exposure to prompt engineering and LLMs (GPT, Claude, Gemini, or similar).

- Based in Bangalore, willing to work five days a week from office (no remote option).

Skills Required

Debugging instinct and genuine LLM experimentation matter more here than any single technical certification — the listing repeatedly emphasizes root-cause analysis and self-directed learning ability over formal qualifications.

- Prompt engineering and hands-on LLM experimentation.

- Basic understanding of speech technologies (STT/ASR and TTS).

- Strong debugging mindset — log inspection and error tracing.

- Familiarity with chatbots/voicebots, even at hobby/project level.

- Clear written and verbal communication for technical and non-technical stakeholders.

𝐏𝐨𝐬𝐭 𝐎𝐯𝐞𝐫𝐯𝐢𝐞𝐰

𝐂𝐨𝐦𝐩𝐚𝐧𝐲 : Kapture CX
𝐑𝐨𝐥𝐞 : AI Delivery Intern
𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 0–1 Year
𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: Bangalore (fully office-based, 5 days/week)
𝐂𝐚𝐭𝐞𝐠𝐨𝐫𝐲: Internships