About Klarity

Klarity (YC S18) is the Enterprise Instinct platform. TL;DR: Series B, $91M raised, 7x growth last year.

Enterprises still rely on consultants to figure out how they operate – months of work, millions spent, and outdated before the ink dries. We built a better way.

Our AI discovers how work actually happens across every team and application, Structures it into a living Context Graph, and Improves it continuously.

ServiceNow mapped 900+ processes in 9 days. DoorDash captured 3,800+ finance operations in 14 weeks, replacing a 2-year engagement. That's not a project. That's compounding intelligence.

OpenAI, Google, DoorDash, and Stripe use Klarity to transform how they transform. We shipped GPT-4 document chat within 12 hours of OpenAI's API launch.

Speed and quality aren't a tradeoff here – they're the standard.

The Role

Generative AI is rapidly commoditizing SQL queries, dashboards, and traditional data analytics. Anyone can write a query now. What AI can't replace is the judgment to know what questions matter, the instinct to connect a qualitative signal from a customer call to a quantitative pattern in usage data, and the conviction to walk into a room and say "here's what we should build next, and here's why."

We're looking for a Product Analytics Engineer who transforms how our product team makes decisions. This is not a service function that waits for data requests. You are embedded in the product organization—working side-by-side with our Director of Engineering, Head of Design, and CTO—proactively pushing insights and recommendations that shape what we build and how we iterate.

You operate across the full spectrum of product intelligence: quantitative analysis of user behavior and feature performance, qualitative analysis of customer conversations and feedback using generative AI, and the strategic judgment to synthesize both into clear product recommendations. You don't provide charts. You provide decisions.

Who You Are

• Maps business outcomes to data, not data to dashboards. You start with the product question, not the query. You understand what success looks like for a feature, define the metrics that prove it, instrument the events to capture them, and interpret the results in the context of business outcomes. When someone asks "how is this feature doing?", you don't just pull numbers—you tell them what the numbers mean and what to do next.

• AI-native analyst who multiplies their reach. You use generative AI tools to do what previously required entire teams. You analyze hundreds of Gong call transcripts to surface recurring pain points. You synthesize NPS feedback, support tickets, and user interviews at scale using LLMs. You treat AI as a force multiplier for qualitative research, not just a SQL copilot.

• Proactive, not reactive. You don't wait for a Jira ticket asking for a chart. You see a drop in activation, dig in before anyone asks, and bring a hypothesis and recommendation to the next planning meeting. You set up alerts, monitoring, and recurring analyses that surface problems and opportunities before the team even knows to look.

• Thinks in experiments, not reports. You design and analyze A/B tests, feature experiments, and rollout strategies. You understand statistical significance, but you also know when to trust directional signal over perfect data. You help the product team build conviction through rapid experimentation, not endless analysis cycles.

• Bridges qualitative and quantitative fluently. You move seamlessly between analyzing PostHog funnels and reading customer interview transcripts. You can spot when quantitative data contradicts what users say (and vice versa) and synthesize both into a coherent story. The best insights come from triangulating across data types, and you do this instinctively.

• Brings energy that elevates the product team. You see messy data and ambiguous signals as puzzles to solve. Your enthusiasm for finding the insight that unlocks a product decision raises the bar for the entire team. You make data-informed decision making feel fast and exciting, not bureaucratic.

• Experience: 4+ years designing and shipping production-grade products

What You'll Do

• Own product analytics end-to-end. Define what we should measure for new and existing features. Instrument events in PostHog, write the analyses, interpret results, and deliver clear recommendations to the product team. You're responsible for the full loop: what to measure → how to capture it → what it means → what to do about it.

• Build AI-powered qualitative research capabilities. Use generative AI to analyze Gong call transcripts, customer feedback, support conversations, and user interviews at scale. Surface thematic patterns, emerging pain points, and feature requests that would take weeks to uncover manually. Make qualitative insight as fast as pulling a dashboard.

• Proactively drive product decisions. Don't wait to be asked. Identify the most important open product questions, design the analysis to answer them, and bring recommendations to the Director of Engineering, Head of Design, and CTO. Your work directly shapes what gets built next.

• Recommend and build new instrumentation. Continuously evaluate what data we're capturing and what we're missing. Propose new event tracking, user properties, and data models that give the product team better visibility into user behavior. You don't just analyze the data we have—you define the data we need.

• Design and run experiments. Partner with product and engineering to design A/B tests, feature flag rollouts, and controlled experiments. Analyze results with rigor but also with speed—help the team learn fast and make decisions confidently.

• Synthesize across data sources into product narrative. Combine quantitative product data, qualitative customer signals, market context, and business metrics into coherent product narratives. Produce weekly and ad-hoc analyses that the leadership team actually reads and acts on.

Our Stack

• Product Analytics: PostHog (our primary analytics platform—event tracking, funnels, retention, feature flags, session replay)

• Backend Database: SQL (PostgreSQL)

• Customer Intelligence: Gong (call recordings and transcripts), customer feedback channels

• AI Tools: We expect you to aggressively use generative AI (Claude, ChatGPT, etc.) to accelerate qualitative analysis, automate recurring analyses, and build internal AI-powered research workflows

• Collaboration: You'll work embedded in the product org, directly alongside the Director of Engineering, Head of Design, and CTO

Benefits

• Equity in addition to competitive cash compensation

• Relocation support to San Francisco Bay Area (where applicable)

• $500 Annual Learning Fund

• $100 Monthly Wellness Fund

• Office-related Perks:

  • BART or Caltrain to the office? Contribute pre-tax funds to a Parking & Transit account, and you will never be taxed for it!

  • Lunchtime, Leveled Up: Enjoy curated local eats.

  • Snack Central: Drinks and snacks for every craving - from healthy bites to Klarity team favorites.

  • Onsite Gym Access: A state-of-the-art fitness center right downstairs, and it's free!

  • Safe & Secure Bike Room: Commute in and safely store your bike.

  • 100% Employer-Paid Medical, Dental & Vision options!

Klarity is an equal opportunity employer. Klarity provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, national origin, sexual orientation, gender identity or expression, age, disability, genetic information, marital status or veteran status.

Compensation Range: $150K - $200K