Babbel Labs is building the future of language learning. We are an AI-first, independent company within the Babbel group, based in Berlin. Our teams bring AI, research and product together to ship experiences that set a new standard for how people learn.
The roleBabbel Labs is looking for a Principal Engineer to own our AI content systems end to end. Starting from nothing, together with our learning content experts, these systems create all of our content: the curriculum itself, and the thousands of exercises built on it, with text, images and audio generated by models and judged by experts.
Your main goal: set a high bar, and design a robust, verifiable system that turns our experts' skills into real outcomes for learners.
This is an Individual Contributor role with influence across Engineering, Content and Product. You design and build the systems yourself, set the technical direction for the engineers working on them, and work closely with the language and curriculum experts who own the quality bar.
We move fast and get things done. When something important comes up, we adapt the roadmap, and you help the team re-plan and keep shipping.
How you'll make an impactDesign and build serverless, event-driven pipelines that generate content at scale and hold up under re-runs, partial failures and cost limits.
Make evaluation the main engineering artifact, so we always know whether generation quality is getting better or worse as prompts and models change.
Design our language experts' judgment into the system: decide what reaches them, capture their decisions as data, and keep human the decisions that must stay human.
Make every generated item traceable and reproducible, from a reviewer's comment back to the exact prompt, model and input.
Set technical direction for the engineers around you through design reviews, pairing and clear decomposition of ambiguous work, without managing them.
Influence product, platform and curriculum leads on what to build next and what to drop.
Work agent-first: ship with coding agents every day and raise how the team verifies their output.
Strong system design, especially serverless and event-driven architectures on AWS or a comparable cloud.
Shipped production LLM applications that real users depended on, with a real evaluation practice behind them.
Built data or content pipelines that handle idempotency, versioning, replay and partial failure.
Led a team technically through a hard deadline or an important change of plan, re-planned with them, and still shipped.
Worked closely with non-engineering domain experts and turned their judgment into system behaviour.
Fluent in Python or TypeScript.
Use coding agents in your daily work, with a habit of verifying what they produce.
Clear communicator who can hold a technical position with engineers, product and domain experts.
Background in computational linguistics, NLP or applied linguistics.
Experience with educational technology or content platforms.
Experience with RAG, retrieval systems or agentic workflows in products.
Experience validating LLM-as-judge setups against human reviewers.
Public technical work: talks, writing or open source.
You are an individual contributor with real influence, not a people manager. Success is measured by what ships, how reliably it runs, and how much faster the team gets because of the systems and standards you put in place.
You work closely with the Content engineers, our language and curriculum experts, and product and platform leads. We are a small, AI-first team in Berlin, working hybrid.
Diversity at BabbelAs part of our ongoing journey towards building a diverse, equitable, and inclusive company, we welcome everyone to apply, especially individuals who are underrepresented in tech. We are a learning company, inside and out, and we encourage you to apply even if you do not fit all the technical requirements — all candidates are assessed based on skills, qualifications, and our business needs. Please state your pronouns in your application, and let us know if you'd like to be addressed by a name other than the one appearing on your official documents. If you have a disability or special need, feel welcome to inform us so we can provide proper assistance in the application process.
Skills Required
- Strong foundation in computational linguistics, natural language processing, or applied linguistics
- Proven success operating at Senior Principal Engineer level or equivalent organisational scope
- Demonstrated ability to influence technical strategy across multiple teams and domains
- Deep experience designing and operating large-scale distributed systems and platform architectures
- Hands-on experience designing, building, and shipping AI/ML systems into production at scale
- Strong understanding of AI evaluation, governance, observability, security, privacy, and operational risk management
- Track record of leading organisation-wide technical initiatives from strategy through execution
- Experience partnering with senior leadership to shape technical roadmaps and investment decisions
- Exceptional communication and stakeholder management skills
- Ability to balance long-term technical vision with pragmatic execution in ambiguous environments
- Proven experience technically leading groups of engineers through execution while remaining an active individual contributor
- Ability to contribute meaningfully to linguistic discussions and content-creation pipelines
- Advanced degree or equivalent professional depth in computational linguistics, NLP, or related discipline
- Experience building AI-enabled content platforms, educational technology products, or knowledge systems
- Experience with retrieval systems, RAG architectures, vector databases, and agentic workflows
- Experience establishing AI governance frameworks and operating models at scale
- Experience with AWS-based architectures and modern cloud-native platforms
- Public technical leadership through conferences, publications, open-source contributions, or industry engagement
What We Do
Babbel is the top-selling language learning platform. Driven by our purpose – to create mutual understanding through language – we build products that help people connect and communicate across cultures. Through self-study lessons with Babbel, instructor-led live classes with Babbel Live, Babbel for Business, our own podcast series, and our magazine, our users can focus on using a new language in real situations with real people. And it works: studies with Yale University, City University of New York, and Michigan State University prove that Babbel gets users to speak with confidence. The key is a blend of humanity and technology. More than 60,000 lessons in 15 languages are hand-crafted by more than 200 linguists, and user behaviour is constantly analysed to shape and improve the learner experience. The Babbel team is as diverse as our content. Based in Berlin, Germany, and New York, USA, 1,000+ Babbelonians from over 80 nationalities represent the diverse backgrounds, characteristics, and perspectives that make each person unique. Building genuine connections with our users is what sets Babbel apart, making it the world's leading language-learning platform with more than 16 million subscriptions sold. Founded in 2007 as the pioneering online language learning platform, we've grown steadily over the years. In 2023, Babbel was honoured with a place on Fast Company's list of the World's Most Innovative Companies, ranking 4th in the Education category
