About Klarion

Klarion is re-inventing customer feedback analytics to make it awesome and accessible to mid-market companies. Our mission is to combine LLM technology with robust feedback analytics to turn mountains of customer feedback into clear, actionable insights that keep customers happy and products sharp. Led by founders with successful exits under their belt, we’re an early-stage AI startup where every line of prompt and code shapes the future of customer experience.

Must-haves

5+ years of hands-on experience in text analytics, thematic analysis, sentiment analysis, entity/attribute extraction and severity/risk signals from text using LLMs or classic text analytics techniques, NLP and ML (experience with pre-LLM AI tech counts).
Applied experience in unstructured customer feedback analysis at scale — transforming unstructured feedback (phone calls, reviews, surveys, qual research, social media posts) into structured, actionable insights.
Experience developing metrics and evaluation frameworks for text analytics and feedback intelligence systems.

Role

Lead the design and development of our proprietary customer feedback analysis engine pulling from and building on techniques for thematic analysis, sentiment classification, and data enrichment. Focus is on descriptive and diagnostic analytics and not predictive analytics.

Key Responsibilities

Text Analytics using LLM: Design, test, and refine LLM-based strategies for extraction of structured insights, themes, sentiment and data enrichments from unstructured conversational data.
Pattern Detection: Develop methods to quantify qualitative data and uncover patterns and drivers of customer experience.
Retrieval & Context strategy (partner with Engineering): Guide development of strategies for optimizing retrieval and context for feedback analytics use cases.
Evals & measurement (partner with Engineering): Guide development of datasets, metrics and rubrics for automated evals of text analytics and feedback insight quality.
Cross-Functional Collaboration: Work closely with founders and engineering team to ship customer-facing features and measure real-world performance.

Qualifications

5+ years of applied AI/data science experience in feedback analysis / qualitative research - transforming unstructured customer feedback into structured, actionable insights. Experience with pre-LLM AI tech counts.
Expertise in text analytics, thematic analysis, sentiment analysis, and enrichment extraction from text using LLMs or classic text analytics techniques, NLP and ML.
Experience developing metrics and evaluation frameworks for text analytics and feedback intelligence systems.
Experience using LLM prompt-engineering techniques in the text analytics / qualitative research domains.
Skills: Python and SQL (used for data manipulation)
Strong written and verbal communicator who can explain trade-offs to both engineers and product leaders.
Nice to have: Experience at VoC / CX platform companies (Qualtrics, Medallia, Gainsight, Sprinkr, etc.)

This Role Is Not for Everyone

If you need perfect specs and predictable days, you’ll hate it here. If you thrive on pace, ambiguity, and the thrill of building something new with massive impact, we’d love to meet you.

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