Product Engineer - m/w/d

Help Us Change the Way the World Works

Build something that matters.

Langdock exists to change the way the world works, bridging the gap between what technology can do and what people actually do with it. We bring all leading AI models into one secure, model-agnostic platform and make them usable across entire organizations. Over 6,000 companies use our platform every day, from fast-growing startups to some of Europe's largest enterprises. Their employees open Langdock to draft strategies, analyze documents, or automate workflows - helping them to work smarter, think more creatively, and reach their full potential.

The role

A Product Engineer at Langdock owns features end to end. You take a customer problem, scope it, design the solution, build it across the stack, ship it, and stay close to it after release.

Product Engineers are close to users. You join customer calls, watch people use the product, read support context, and use that input to decide what should exist and how it should behave. This gives you a lot of product influence. The person building the feature is expected to shape the feature.

We are deliberately resource-constrained. For most reasonable feature ideas, the question is not whether we should build them, but when. Product Engineers are the people who turn that prioritization into shipped product quickly, without lowering the bar.

From a product perspective, we like how companies like Linear build software: intuitive, efficient and with a high quality standard. The bar is not just whether a feature works. The bar is whether it feels inevitable. We want that level of product taste while solving a much more complex AI and enterprise problem.

What you will work on

You will work across our main product surfaces: Chat, Agents, Workflows, Mobile and admin tooling. Examples of the kind of projects Product Engineers have led:

• Evals for agents. We need infrastructure and product surfaces that let us evaluate agent behavior, compare runs, catch regressions, and help customers trust what agents do.

• Library, a system for organizing attachments and files uploaded across the platform. The challenge is not only storage; it is making user and workspace knowledge retrievable, understandable, and governed over time.

• Governance for agents in enterprise workspaces. Admins need to manage agents at scale: who can create them, who can use them, how they are shared, how they are audited, and how they fit into existing security policies.

• Excel and Outlook plugins that bring Langdock into the tools enterprise users already live in.

• The Langdock Workflows product, which allows users compose multi-step automations with agents, conditions, loops, structured outputs, and human-in-the-loop nodes.

You will pick up an area of the product to work on over time and shape where it goes next.

Tech stack

• TypeScript across a Turborepo monorepo

• Next.js, React, Tailwind on the front end

• Node.js, PostgreSQL with Prisma (and pgVector), Redis with BullMQ on the back end

• React Native and Expo for the mobile app

• Linear for ticket management

• Datadog and Sentry for observability

You should be familiar with most of this. We trust you to pick up the rest quickly.

How we ship

• Small temporary squads of 2 to 3 engineers around a topic. Squads form, ship, and dissolve.

• Every change is linked to a Linear ticket and ships via PR. CI runs lint, tests, and AI review. One human review is required.

• We deploy continously to production.

• Engineers have the opportunity to join customers on-site, to sit with real users during hackathons or workshops

• We use AI tools heavily in engineering. You have freedom in the tools to use (eg. Cursor, Claude, Codex). We are building a strong harness that allows engineers to move fast while shipping high quality software.

• We are building a strong operating system around AI-assisted shipping: clear ticket context, focused branches, AI review before human review, screenshots or videos for product changes, and production verification after release.

• The engineer who ships a change owns it in production. If something breaks, you lead the fix.

What we are looking for

• 3 to 6 years of full-stack experience shipping production software people actually use.

• Strong in TypeScript, React, and Node. Comfortable with Postgres, Redis, queues, and async work.

• Very driven. You have high standards for yourself, move fast without needing to be pushed, and want to do the best work of your career.

• Close to users. You want to understand why people behave the way they do, and you use that understanding to make product decisions.

• Able to take a vague problem to a shipped feature. You scope, decide, implement, test, and iterate.

• A working understanding of how LLMs behave: context windows, tool calling, streaming, and the differences between major providers.

• Heavy user of AI tooling in your own development workflow, with opinions on what works and what does not. We are looking for people who are already compounding their output with AI.

• Demonstrated ability to ship things end to end: side projects, open source, products with real users, or something equivalent.

Working here

We work from one office in Berlin, Greifswalder Str. 212. Engineering is fully in person; we believe the hardest problems get solved faster at a whiteboard than in a Slack thread.

Most engineers start around 8:30. Lunch and dinner are together when people stay. Running and gym are part of the routine for many of us.

Compensation

Top of market, transparent levels, all roles include equity. Levels are tied to scope, not negotiation or years of experience. We narrow down the range early in the process.

Next steps

If this sounds like your kind of work, we would like to meet you.

We move fast. Most processes complete within two weeks.