Developer Growth, API & Agentic AI Products

DeepL•Austin, TX

1d•Hybrid

About The Position

The DeepL API team is helping shape one of the company's most important strategic priorities: making DeepL the translation layer inside the tools people already use and the products developers build. As AI assistants like Microsoft Copilot, Claude, and ChatGPT become embedded in everyday workflows, the question is no longer "How good is your translation?" but "Do you have an MCP?" We're building DeepL's presence across MCPs, CLIs, agent skills, prompt libraries, and marketplace integrations to ensure developers reach for DeepL first when building agentic workflows. As part of the API Product Marketing team, you'll work at the intersection of Marketing, Product, and Engineering, partnering closely with API Product Managers and Engineering leaders to help define a rapidly evolving category. This is not a traditional DevRel team—we're focused on driving adoption, shaping ecosystem strategy, and helping DeepL become the default translation layer for the next generation of AI-powered products.

Requirements

Significant hands-on experience building with AI agents, copilots, developer tools, or related ecosystems
Experience creating technical content that developers actively use and trust
Strong understanding of developer workflows, APIs, integrations, and automation
Ability to work cross-functionally with Product, Engineering, Marketing, and Partnerships teams
Demonstrated ability to identify ecosystem trends and translate insights into action
Excellent written and verbal communication skills
Experience creating code samples, technical documentation, or developer-facing resources

Nice To Haves

Experience with MCP, Copilot plugins, Claude tools, ChatGPT integrations, or similar ecosystems
Familiarity with localization, translation technology, or language AI solutions
Existing presence within developer communities or technical creator networks
Experience optimizing technical content for AI-assisted discovery and retrieval
Background in developer advocacy, developer marketing, product marketing, or developer-facing roles at API, infrastructure, or SaaS companies

Responsibilities

Drive DeepL's headless distribution surfaces
Partner with Engineering, Design, and Product to ensure DeepL's MCP and CLI fit naturally into how developers build, ship, and integrate agentic workflows
Drive MCP discoverability across the Claude ecosystem, ChatGPT, Microsoft Copilot, and emerging agent marketplaces
Drive CLI adoption through package registries (npm, pip, Homebrew), GitHub visibility, developer toolchains, CI/CD examples, and starter kits
Work with the Partner team to incorporate MCP and CLI surfaces into hyperscaler marketplaces and co-sell motions
Monitor the agentic tooling and developer ecosystem, identify emerging distribution opportunities, and bring ecosystem intelligence back to Product and Engineering
Own the headless activation funnel
Instrument the activation funnel end-to-end, from MCP install or CLI OAuth through first successful translation and first paid character
Shape the free-tier strategy, onboarding experience, and adoption patterns that optimise conversion
Identify and remove the highest-friction step in the funnel, bringing structural issues back to Product and Engineering with evidence
Report on the headless funnel as a leading indicator of ecosystem growth and adoption
Build the artefacts developers reach for
Create prompt libraries, agent templates, implementation examples, and integration guides that make DeepL the obvious choice for agentic builders
Develop workflow documentation showing how DeepL's glossary, style, and customisation capabilities combine with agentic patterns in ways native LLM translation cannot replicate
Build code samples and reference integrations that demonstrate production-quality usage, not toy demos
Identify capabilities and opportunities that could unlock additional value for developers
Create content that demonstrates practice, not features
Create content that demonstrates where developers verify output, when they trust it, and how they combine DeepL with agentic workflows to achieve results native LLM translation cannot reproduce
Show what production-grade implementations look like versus integrations that fail under real-world conditions
Write, record, and publish content across GitHub, Discord, LinkedIn, developer newsletters, and other relevant channels
Structure technical content so it is discoverable by both developers and AI coding assistants
Build distributed ecosystem presence
Participate meaningfully in the communities where agentic developers work as a credible practitioner
Amplify developers already building with DeepL through showcases, workflow breakdowns, and collaborative content
Build relationships with creator-developers and ecosystem voices whose audiences overlap with DeepL's target builder cohorts
Strengthen DeepL's presence and trust across the surfaces where developers discover and evaluate tools
Shape the product from the outside in
Gather signal from MCP communities, GitHub discussions, AI ecosystems, and developer feedback
Identify emerging integration patterns, ecosystem needs, and gaps in DeepL's current API surface
Understand where DeepL wins and loses against native LLM translation workflows and why
Translate ecosystem insights into actionable input for the product roadmap