AI Product Analyst Intern
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Summary
Intern role at RevRag AI in Bengaluru: analyse production Voice AI and in-app AI agent conversations to find failures across the STT/TTS, LLM, retrieval, and telephony pipeline, track KPIs, run A/B tests, and build dashboards using SQL, Python, and BI tools for product, engineering, and business teams.
About the role
We are looking for an AI Product Analyst Intern who enjoys digging into data, understanding AI systems, and solving product problems. You will work closely with the Product, AI Engineering, and Business teams to analyse how our AI agents perform in production, identify where conversations or workflows break down, measure product health, and build dashboards that help teams make better decisions.
This role is intentionally broader than a standard product analyst: you become the health monitor for our AI platform, tracking everything from model quality (STT, TTS, SLMs, LLMs) and telephony reliability to product workflows and business KPIs, then turning those insights into actionable improvements for engineering and product teams. It is an ideal role for someone interested in Product Management, AI, Analytics, and Data.
What Youll Do
- Analyse production AI conversations across Voice AI and In-App AI Agents.
- Identify where users drop off or where AI responses fail.
- Investigate failures across the entire AI pipeline: Speech-to-Text, Text-to-Speech, voice-to-voice models, Small Language Models, LLM reasoning, retrieval and memory, the telephony pipeline, and Action Intelligence.
- Work with Product and AI teams to identify root causes of quality issues.
- Track product health metrics and recommend improvements.
- Build dashboards for Product, Business, and Engineering teams.
- Define and monitor KPIs across different AI systems.
- Analyse customer journeys and identify friction points.
- Measure conversation quality, latency, task completion, and automation success.
- Generate insights from production data to improve customer experience.
- Assist in A/B testing new AI models and product features.
- Document recurring issues and suggest long-term improvements.
Example Problems Youll Solve
- Why are users abandoning a conversation after 30 seconds
- Which STT model performs best across different accents
- Which TTS voices produce the highest engagement
- Why did an AI workflow fail to complete
- Which telephony providers have higher call failure rates
- Where are AI agents hallucinating or misunderstanding user intent
- Which product flows generate the highest drop-offs
- Which enterprise customers experience the most AI failures
- Which AI models should be replaced or fine-tuned
- What are the biggest contributors to latency across the AI pipeline
Dashboards Youll Build
Youll design and own dashboards including:
- AI Quality and Product Health
- Voice Pipeline and Conversation Analytics
- Customer Journey and Model Performance
- Telephony Reliability and Business KPIs
- Error and Failure Analytics
- AI Cost vs Performance
What Were Looking For
- Strong analytical and problem-solving skills.
- Comfortable working with large datasets.
- Basic SQL knowledge.
- Python for data analysis (preferred).
- Understanding of product analytics.
- Familiarity with dashboards (Metabase, Power BI, Tableau, Looker Studio, and similar).
- Curiosity about AI and large language models.
- Strong communication skills and the ability to work with cross-functional teams.
Bonus Points
- Experience with AI or LLMs.
- Understanding of speech technologies (ASR, STT, TTS).
- Knowledge of prompt engineering.
- Experience with conversational AI.
- Familiarity with product analytics tools such as Mixpanel, Amplitude, or PostHog.
- Basic understanding of APIs and backend systems.
Who Should Apply
- Students or recent graduates pursuing Computer Science, Data Science, AI/ML, Analytics, Information Systems, or related fields who enjoy understanding how products work, analysing data, and improving AI systems.
About RevRag AI
RevRag AI is a Bengaluru-based deep-tech startup building production-grade Voice AI and LLM-powered automation for customer-facing workflows. Our multilingual, in-app AI agents plug directly into BFSI journeys, improving digital onboarding, sales, and support while cutting operational cost by up to 70%.
We work with leading BFSI organisations including Mahindra Finance, Motilal Oswal, PayTM Insurance, PhonePe, KreditBee, Razorpay, Udaan Capital, Kissht, PolicyBazaar, InsuranceDekho, Open Capital, and EaseBuzz.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.