Developer Growth | API & Agentic AI Products

The work that compounds fastest is not conference talks or blog posts — it is the repository someone forks, the prompt template embedded in a starter kit, the implementation example a coding assistant returns when asked how to add translation or speech to an agentic workflow. Your job is to create those artefacts and to provide suggestions for capabilities that could unlock more value, including:

Prompt libraries and agent templates that make DeepL the obvious choice for agentic builders — across text translation, speech-to-text, and speech-to-speech

Implementation examples and integration guides structured for both human readers and AI retrieval — when a developer asks their coding assistant how to add translation or voice to an agent, DeepL should be the answer it surfaces

Workflow documentation showing how DeepL's glossary, style rules, and customisation capabilities combine with agentic patterns in ways a native LLM translation cannot replicate — and how speech-to-text and speech-to-speech extend those patterns into voice-driven workflows

Code samples and reference integrations that demonstrate production-quality usage, not toy demos

Feedback from the build: where DeepL's API, MCP, and CLI surfaces don't support emerging agentic patterns cleanly, bring that back to product and engineering as concrete roadmap input — you will often be the first person to hit the sharp edges

The scarce skill in developer content right now is not explaining what an API does — any model can do that. It is showing how a thoughtful practitioner actually uses it: where they pause, what they verify, when they trust the output and when they don't, and what a production-grade integration looks like versus one that will break under real conditions. And developers no longer discover that content through branded hubs — they find it on GitHub, Discord, Reddit, LinkedIn, and developer newsletters, and increasingly through what their AI coding assistant recommends. The what and the where are one job:

Write, record, and publish content that shows witnessed practice — how DeepL's translation and voice capabilities combine with agentic workflows to get results a native LLM cannot reproduce — for an audience building production systems

Participate meaningfully in the communities where agentic developers work — not as a brand voice, but as a credible practitioner

Amplify the developers already building with DeepL through implementation showcases, workflow breakdowns, and collaborative content that surface real usage

Build relationships with creator-developers and ecosystem voices whose audiences overlap with DeepL's target builder cohorts

Feedback from the ecosystem: relay what builders are asking for in MCP forums, GitHub issues, and community threads — and where DeepL loses to native LLM translation in a developer's evaluation, and why — back to product and engineering as the person with the clearest view of what the ecosystem needs next

Required Qualifications

Deep hands-on experience with agentic tooling. You have built integrations using MCP, Claude tools, Copilot plugins, or similar — real production artefacts, not demos. You know the MCP ecosystem from the inside: the protocol, the tooling landscape, where the sharp edges are, and why the good implementations look the way they do.

Taste and judgment about AI-generated output. The specific thing DeepL offers over asking an LLM to translate — glossary adherence, style consistency, audit trail, European fluency at scale — only matters if you can demonstrate it credibly to someone actively evaluating alternatives. That requires being able to evaluate translation quality yourself, not just describe the features that are supposed to produce it.

Content that practitioners trust. Not product marketing. Not feature announcements. The kind of content a senior developer saves and references three months later because it helped them understand something real. You can write, and you can also ship a repository that makes the same argument in code.

Effective operation at the intersection of product, engineering, and market. You are not waiting to be told what to build or say. You read the ecosystem, form a point of view, and act on it — while keeping product and engineering close enough that your external work and their internal roadmap reinforce each other rather than diverge.

Credibility in the translation and language domain. You do not need to be a linguist. You do need to understand why glossary adherence matters in a legal workflow, why style rules matter in a brand context, and why "the LLM can just translate it" is an argument with a real answer — and be able to make it clearly to a sceptical developer.

A practitioner's instinct for distributed presence. You understand that developer discovery happens across GitHub, Discord, Reddit, creator content, and AI assistant recommendations — not inside a branded hub. You know how to be genuinely useful across those surfaces rather than broadcasting into them.

Preferred Qualifications

Direct experience shipping integrations into Copilot, Claude tools, or the ChatGPT plugin ecosystem

Hands-on experience with voice and speech products — speech-to-text or speech-to-speech APIs, real-time audio pipelines, or voice agent frameworks

Familiarity with localisation toolchains, TMS, or CAT tools

An existing presence in agentic developer communities — GitHub, Discord, Substack, or similar — where your work is already known

Experience structuring technical content for AI-searchable discoverability

Background in a developer-facing role at a B2B API or infrastructure company (translation experience not required; infrastructure instincts are)

Diverse and internationally distributed team: joining our team means becoming part of a large, global community with people of more than 90 nationalities.

Open communication, regular feedback: we value smooth collaboration, direct and actionable feedback, and believe that leading with empathy and growth mindset makes us better together.

Hybrid work, flexible hours: we offer a hybrid work schedule, with several days in the office each week.

Virtual Shares: every employee receives Virtual Shares, linking your contribution directly to DeepL's growth.

Regular in-person team events: we bond over vibrant events that are as unique as our team.

Monthly full-day hacking sessions: every month, we have Hack Fridays.

30 days of annual leave: we value your peace of mind.

Competitive benefits: tailored to your unique location.

If this role and our mission resonate with you, but you're hesitant because you don't check all the boxes, don't let that hold you back. At DeepL, it's all about the value you bring and the growth we can foster together. Go ahead, apply—let's discover your potential together. We can't wait to meet you!

#LI-TB1

You are welcome at DeepL for who you are - we appreciate authenticity here. Our product is for everyone, and so is our workplace. The more voices we have represented and amplified in our business, the more we will all succeed, contribute, and think forward! So bring us your personal experience, your perspectives, and your background. It’s in our diversity that we will find the power to break down language barriers in the world.