Staff Software Engineer | Developer Experience at Deepl
- Company: Deepl
- Location: London
- Employment type: Full Time
- Posted: 2026-08-28
Meet DeepL DeepL is a global AI product and research company focused on building secure, intelligent solutions to complex business problems. Over 200,000 business customers and millions of individuals across 228 global markets today trust DeepL's Language AI platform for human-like translation, improved writing and real-time voice translation. Founded in 2017 by CEO Jaroslaw “Jarek” Kutylowski, DeepL now has around 1,000 passionate employees and is supported by world-renowned investors including Benchmark, IVP, and Index Ventures. Our goal is to become the global leader in trusted, intelligent AI technology, building products that drive better communication, foster connections, and create a meaningful impact. To achieve this, we need talented people like you to join our journey. If you’re ready to shape the future of AI and grow your career in a fast-moving, purpose-driven environment, DeepL is your next destination. What sets us apart What sets us apart is our blend of cutting-edge AI technology, meaningful work, and a culture where people truly thrive. We’re a team of innovators, researchers, and creators driven by a shared purpose to unlock human potential by making work simpler, smarter, and more connected. When we share what it’s like to work at DeepL, the reactions are overwhelmingly positive. This might be because of our technology that helps millions of people and businesses communicate and work better every day, or because of the trust, curiosity, and care that shape our culture. What we know for sure is this: being part of DeepL means joining a team dedicated to innovation, growth, and well-being. Discover more about life at DeepL on LinkedIn , Instagram , and our Blog . Meet the team behind this journey You will join the Developer Experience track, whose customers are DeepL's own engineers. Every change that reaches our products, from a research prototype to a production release, travels through the platform, pipelines and workflows this track owns. Our job is to make that journey fast, safe and obvious, so that engineers spend their time on the problems only they can solve. That ownership runs the full width of the developer's day. It covers the foundation: source control, the CI and CD fleet that runs every pipeline across Kubernetes, macOS and Windows, build and dependency caching, and the artifact and package registries that hold what we ship. Having recently moved our source and CI onto GitLab SaaS, we are now shaping what a genuinely self-service platform looks like on top of it. It also covers everything an engineer actually touches: our internal developer portal and service catalogue in Backstage, the Golden Path templates and release automation that make the right thing the easy thing, automated guardrails for security and production readiness, self-service access management, and the AI tooling our engineers use every day, including AI-assisted code review. We measure whether any of it is working, through developer surveys and delivery metrics. We treat developer experience as a product, not a support function. We are opinionated about paved roads, allergic to mandates without migration paths, and increasingly focused on a question the whole industry is still answering: what does an engineering organisation look like when AI is a first-class part of how software gets built? Your responsibilities Own technical direction for a significant part of the Developer Experience mandate. Identify where the biggest friction sits for our engineers, form a clear position on how to remove it, and see that work through to adoption. Lead initiatives that lift developer productivity across multiple engineering teams, by understanding and improving processes and tooling, and by drawing on both established software engineering practice and AI capability. Design and build the workflows and tooling that carry a change through the software development lifecycle, from local development through review to release. Lead our work on AI across that lifecycle. Evaluate what genuinely helps, build the guardrails that make it safe and useful at our scale, and be candid about what does not work. Treat internal developers as customers and grow a community around developer experience. Talk to them, watch where they struggle, and let evidence decide what to build and whether it landed, whether that evidence is survey data, delivery metrics or support load. Empower product teams to own their delivery journey, and turn consensus across engineering into shipped change. Much of the work at this level is influence without authority. Define standards that hold across the track and drive migrations to them, bringing teams along with a working path rather than a deadline. Mentor engineers across the track and raise the technical bar of the group, through design reviews, architecture decisions and the everyday habits that keep systems maintainable. Share in operating what we build, including a sustainable on call rotation for the
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