Product Marketing Engineer

1 нед. назад

GermanyEuropeHybrid

sdkdocker

Role involves hands-on use of product to clearly explain it to engineers and become a voice for .

Обязанности

Become a subject matter expert across tracing, evals, prompt management, datasets, metrics, self-hosting, and the broader AI engineering workflow
Create product and technical marketing content — blog posts, deep dives, benchmarks, launch videos, social, conference talks — that translates technical nuance into clear value propositions for developers and teams
Make our documentation, guides, and examples the best in the category, including demo apps, code samples, and workshop material that users can actually run
Speak at, organize, and attend high-signal in-person events for AI engineers, and turn each one into reusable product education: talks, demos, workshop repos, and follow-up content
Own the content strategy and roadmap, informed by competitive and market analysis across LLM observability, evals, and agent tooling, plus metrics on what is actually working
Partner closely with product, engineering, the ClickHouse product marketing team, sales, solutions, and support to launch new capabilities with sharp positioning and product communication grounded in real customer problems

Требования

You have 5+ years across engineering, data science, DevRel, technical product marketing, technical writing, or developer tools — exact title matters less than work quality, as long as you can go deep on the product.
You write exceptionally well, with taste and strong opinions about what makes technical content useful. You make complex ideas feel simple without making them shallow.
You can code enough to build examples, inspect SDKs, and understand traces, and you stay close to what developers are actually building — enough to be credible with strong engineers.
You can advocate for a technical product in person and in writing, comfortable explaining why something matters rather than only how it works.
You can own projects end to end, from messy input to shipped public assets.
You collaborate well across product, engineering, marketing, sales, solutions, support, and ClickHouse counterparts.
A strong plus:
You already create content — blog posts, videos, talks, newsletters, docs, technical explainers — and have an audience, or clear evidence that experienced technical people value your explanations.
You are deep in LLM applications, agents, evals, prompt engineering, RAG, and observability.
You have run benchmarks, written competitive deep dives, or produced opinionated technical market analysis.
You have spoken at technical events, organized developer events or workshops, contributed to open source, or built a community around a technical product — and you are comfortable on camera and on stage.

Другое

Open Source LLM Engineering Platform that helps teams build useful AI applications via tracing, evaluation, and prompt management ( mission , product ). We are now part of ClickHouse.
We're building the "Datadog" of this category; model capabilities continue to improve, but building useful applications is really hard, both in startups and enterprises.
Largest open source solution in this category: trusted by 19 of the Fortune 50, >2k customers, >26M monthly SDK downloads, >6M Docker pulls.
We joined ClickHouse in January 2026 because LLM observability is fundamentally a data problem and already ran on ClickHouse. Together we can move faster on product while staying true to open source and self-hosting, and join forces on GTM and sales to accelerate revenue.
Previously backed by Y Combinator, Lightspeed, and General Catalyst.
We're a small, engineering-heavy, and experienced team in Berlin and San Francisco. We are also hiring for engineering in EU timezones and expect one week per month in our Berlin office ( how we work ).
Workplace: Europe: Remote, with 3–5 days together in Berlin every two months. US: Fully remote. San Francisco preferred, but we're open to exceptional candidates anywhere in the US.
We are hiring a Product Marketing Engineer to become one of the clearest voices on — someone who can use the product hands-on and can explain it to the engineers building with it.
This is a technical product advocacy role. You will write deep dives and launch content, build demos, make the docs genuinely good, speak at events, and shape how AI engineering teams think about observability, evals, and prompt management. You will also carry what you learn from users and the market back into how we position the product.
The best fit is an (previous) engineer or highly technical product marketer who wants to educate through content — technically strong enough to hold a real conversation with serious AI engineering teams, not just describe features. It's a strong plus if you already write publicly, have an audience, contribute to open source, or hold original opinions that experienced AI engineers care about.
If you mainly want an events-and-community role, our Developer Relations Engineer (Events & Community) role is the better fit.
sits inside real AI engineering workflows, which means our marketing has to clear a higher bar: strong engineers should find it genuinely useful, not just accurate. In practice that looks like clear explanations, good demos, runnable examples, honest technical tradeoffs, docs that people bookmark, and launch material with a strong point of view.
This role sits between the product and the market. You should be able to understand how a feature works, explain why it matters, build the examples that proves it, and turn what customers and the community are asking into sharper product communication.
We can run the full process to your offer letter in less than 7 days ( hiring process ).
We run a TypeScript monorepo: Next.js on the frontend, Express workers for background jobs, PostgreSQL for transactional data, ClickHouse for tracing at scale, S3 for file storage, and Redis for queues and caching. You should be familiar with a good chunk of this, but we trust you'll pick up the rest quickly ( Stack , Architecture ).
Link to handbook
We trust you to take ownership ( ownership overview ) for your area. You identify what to build, propose solutions (RFCs), and ship them. Everyone here thinks about the user experience and the technical implementation at the same time. Everyone manages their own Linear.
You're never alone. Anyone from the team is happy to go into a whiteboard session with you. 15 minutes of shared discussion can very much improve the overall output.
We implement maker schedule and communication. There are two recurring meetings a week: Monday check-in on priorities (15 min) and a demo session on Fridays (60 min).
Code reviews are mentorship. New joiners get all PRs reviewed to learn the codebase, patterns, and how the systems work ( onboarding guide ).
We use AI as much as possible in our workflows to make our users happy. We encourage everyone to experiment with new tooling and AI workflows.
This role puts you at the forefront of the AI revolution, partnering with engineering teams who are building the technology that will define the next decade(s).
This is an open-source devtools company. We ship daily, talk to customers constantly, and fight for great DX. Reliability and performance are central requirements.
Your work ships under your name. You'll appear on changelog posts for the features you build, and during launch weeks, you'll produce videos to announce what you've shipped to the community. You’ll own the full delivery end to end.
We're solving hard engineering problems: figuring out which features actually help users improve AI product performance, building SDKs developers love, visualizing data-rich traces, rendering massive LLM prompts and completions efficiently in the UI, and processing terabytes of data per day through our ingestion pipeline.
You'll work closely with the ClickHouse team and learn how they build a world-class infrastructure company. We're in a period of strong growth: is growing organically and accelerating through ClickHouse's GTM. ( Why we joined ClickHouse )
If you wonder what to build next, our users are a Slack message or a Github discussions post away.
You’re on a continuous learning journey. The AI space develops at breakneck speed and our customers are at the forefront. We need to be ready to meet them where they are and deliver the tools they need just-in-time.