AI Product Engineer

Responsibilities

• Owning products and features from

Benefits

Additional Information

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all - autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don't tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not now? We want to build a lot of products; we can't do that shipping at a normal pace. We've built the company around small teams - autonomous, highly-efficient groups of cracked engineers who can outship much larger companies because they own their products end-to-end. Time for building: Nothing gets shipped in a meeting. We're a natively remote company. We default to async communication - PRs > Issues > Slack. Tuesdays and Thursdays are meeting-free days , and we prioritize heads down building time over perfect coordination. This will be the most productive job you've ever had. Ambition: We want to solve big problems. We strongly believe that aiming for the best possible upside, and sometimes missing, is better than never trying. We're optimistic about what's possible and our ability to get there. Being weird: Weird means redesigning an already world-class website for the 5th time. It means shipping literally every product that relates to customer data. It means building an objectively unnecessary developer toy with dubious shareholder value. Doing weird stuff is a competitive advantage. And it's fun. Who we're looking for We're looking for a full-stack engineer who knows how to leverage LLMs to make PostHog 10x more powerful. You've built and shipped agentic AI applications before and understand it's more than just hitting an API with a good prompt. You'll fit right in if you: Ship end-to-end AI apps - from backend infra to frontend UX. Collaborate widely - work across teams, find the right people, and make progress fast. Think like a product builder - care about users and outcomes, not just code. If you've worked in autonomous agents, workflow automation, or AI copilots before, you'll feel at home, but here you'll get to build it from scratch, in the open, with massive impact. What makes this role unique In this role, you're not hacking together an AI agent hoping someone will use it, you're building on top of a firehose of real customer data with immediate impact, whether that means creating new AI-powered tools or building observability features that help others understand how their agents perform in the wild. Impact from day one: You're building agents on top of real customer data, not toy demos, not "when we get users." Data advantage: PostHog already collects all the context agents need to be useful: analytics, sessions, events, feature flags, and more. You'll build on top of it all. Agents that matter: Instead of copilots on the side, you'll create background agents embedded into engineering workflows - changing how software gets built. Or, you might focus on building the analytics and observability layer around those agents - surfacing insights, clustering behaviors, and measuring model quality so teams can improve their own AI systems with confidence. Build in the open: Work with feedback from the largest open-source product engineering communities in the world.

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