Senior Principal Engineer – AI Content Systems (all genders)
Babbel
| Company | Babbel |
| Category | Engineering |
| Location | Berlin |
| Remote | Hybrid |
| Employment | Not stated |
| Level | Lead |
| Salary | Not stated by the employer |
| Posted | 21 Jul 2026 |
| Last verified | 9 Aug 2026 |
| Source | Employer ATS (ashby) |
Description
ABOUT BABBEL LABS
Babbel Labs is building the future of language learning. We're an AI-first, independent company within the Babbel group, based in Berlin. Our teams bring AI, R&D and product together to ship experiences that set a new standard for how people learn.
YOUR LEARNING JOURNEY IN THIS ROLE
Babbel Labs is looking for a Senior Principal Engineer to define and drive the long-term technical strategy for AI-powered content systems across the organisation.
This is a Senior Principal-level Individual Contributor role with organisation-wide scope. You will own the technical direction for AI-powered content systems and lead the work across multiple teams, products, and domains.
You will combine strategic leadership with hands-on technical impact through architecture ownership, design reviews, coaching, prototyping, and direct involvement in the most complex challenges.
Working across AI, content, product, and platform engineering, you will define the technical vision, establish shared standards, align teams around key decisions, and ensure that AI-enabled systems are scalable, reliable, secure, and measurable in their impact on both the business and learner outcomes.
How You'll Make an Impact
- Define and drive the long-term technical strategy for AI-powered content systems, ensuring alignment with Babbel Labs' business objectives and product vision.
- Shape architectural direction across multiple teams and domains, making key decisions on platforms, tooling, AI infrastructure, and build-versus-buy approaches that will influence how AI capabilities are developed and scaled.
- Lead the design of robust frameworks for AI evaluation, quality measurement, governance, observability, security, and operational reliability, enabling the responsible adoption of AI across the organisation.
- Partner closely with senior leaders across Engineering, Product, Content, and Data to translate strategic priorities into executable technical roadmaps and investment decisions.
- Identify organisation-wide technical risks, dependencies, and opportunities early, helping teams navigate ambiguity and make effective long-term decisions.
- Establish engineering standards, architectural principles, and operating practices that enable multiple teams to move faster while maintaining quality, security, and reliability.
- Mentor and support Principal and Senior Engineers, raising the overall technical capability of the organisation through coaching, design reviews, and technical leadership.
- Lead and contribute to the most complex technical initiatives, remaining close enough to the technology to guide critical architectural decisions and unblock challenging technical problems when needed.
- Provide hands-on technical leadership to delivery teams by translating strategic requirements into clear technical direction, supporting work decomposition, guiding implementation, and unblocking complex delivery challenges.
YOUR SKILLS AND QUALIFICATIONS
- Strong foundation in computational linguistics, natural language processing, or applied linguistics, with the ability to contribute meaningfully to linguistic discussions and understand the role of linguistics in content creation pipelines.
- Proven success operating at Senior Principal Engineer level, or equivalent scope, within a technology organisation.
- Demonstrated ability to influence technical strategy across multiple teams, products, or business 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 — not just strategy or oversight, but direct technical contribution to model development, infrastructure, and productionisation under real product constraints.
- Strong understanding of AI evaluation, governance, observability, security, privacy, and operational risk management.
- Track record of leading organisation-