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PostHog

Context Engineer

Reposted 9 Days Ago
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Remote
Hiring Remotely in USA
Mid level
Remote
Hiring Remotely in USA
Mid level
Create and maintain knowledge bases and context pipelines, build and ship LLM-powered agents and AI tooling, produce technical content for developers, and design docs-as-code systems to keep docs and agent context up-to-date.
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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:

  1. Product-led. More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit.

  2. 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.

  3. 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

This role combines technical content and AI engineering. You'd be a Context Engineer on the Wizard & Docs team.

Your primary responsibilities:

  • Make technologies explainable and legible to both humans and agents

  • Maintain and design knowledge bases

  • Engineer and orchestrate context pipelines

  • Build and ship agents powered by the above

You'll spend your days switching between prose and code – often in the same hour. You’ll create content for humans and context for agents, and the line between those two audiences is disappearing fast.

The work is inherently multidisciplinary. From our experience, the people who are good at context engineering tend to be natural teachers or strong writers who can code at a high level. There's more liberal arts to building robots than you might expect.

Specifically, we're looking for people who:

  • Excel at teaching and communication. You’re great at educating people by explaining technology in a hands-on and illustrative way. Your preferred medium might be writing, building apps, making visuals, or recording video. Whatever it is, you can take a complex system, teach it clearly, and then build it.

  • Have real development chops. You have full-stack software development experience either in full-time roles, side projects, open source, whatever. We welcome all backgrounds, but the technical bar is high. We run production services, ship PRs across multiple codebases and infrastructure, manage a support queue, and get tagged by engineers for code review.

  • Are multidisciplinary. You think laterally and enjoy approaching problems from different angles, switching hats as the work demands: writing docs, shipping code, organizing IA, creating diagrams, building agents or CI/CD pipelines. You're looking for a role that lets you flex all these muscles, where a wide skillset is valued.

  • Think in systems. You won't just write a doc and move on. You'll think about how that doc gets turned into a skill, how an agent executes it, and what happens when the underlying product changes. The whole pipeline is your problem.

  • Build agents and AI tools. You already have experience building on top of LLMs and have strong opinions about what works with regards to the context window, harnesses, coding agents, and more.

  • Bias to action. We ship fast (like, weirdly fast). There's rarely a blueprint to follow, or a list of jobs to be done here. You need to be comfortable being reactive, iterating quickly, and shipping PRs as priorities change.

What you'll be doing

We’re building a self-driving AI product on top of a large collection of dev tools, so the surface area of problems we help solve is huge.

This means you’ll be:

  • Working on our AI Wizard, an AI agent that onboards thousands of users to PostHog

  • Building custom agents, harnesses, skills, context pipelines, and MCPs and shipping them to production

  • Building systems to maintain our developer docs and knowledge bases using docs-as-code and AI engineering techniques

  • Creating technical content across multiple mediums like docs, example apps, or video explainers

  • Creating workflows for publishing streams like the changelog

  • Working with other teams so they can build on top of our systems

Example projects

  • AI Wizard – an AI onboarding agent that onboards all users to PostHog

  • Writer agent – a RAG powered agent system that maintains our docs

  • Context mill – a skill assembly and context delivery service

  • Developer docs – the company’s knowledge base

What you won't be doing

❌ Gathering specs and interviewing SMEs to write reference docs

❌ Running webinars. Eugh, just no

❌ Writing newsletters and brand content

❌ Waiting to be told what to do. No one will hand you a list of tasks or projects to build

You might fit this role if you’re…
  • A technical writer who regularly ships code and builds features

  • A developer advocate who builds as much as they write

  • A software engineer who’s looking to change track

  • A solutions or growth engineer who enjoys creating educational content

  • An instructional or content designer who is technically gifted

  • Or something else, but you have these traits and skills

We're a team of ex-technical writers, ex-software engineers, ex-devrel, ex-PMs, and a bunch of other past lives. We ditched the old titles because the work doesn't map to any of them. We call ourselves context engineers now, and we're still figuring out what that means.

Requirements
  • Software development experience. It doesn’t have to be formal, but you'll be writing production code, not just code samples

  • Proficiency working with LLMs, coding agents, MCPs, and the latest AI engineering tools

  • A portfolio of technical content (personal website, GitHub profile, YouTube channel, zip file, etc.)

  • Excellent writing and communication skills

  • Experience creating educational content for developers

  • An opinionated take on what makes great docs for humans and AI

#LI-DNI

HQ

PostHog San Francisco, California, USA Office

San Francisco, CA, United States

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