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We are looking for an experienced Principal Software Engineer (Fullstack, AI) to join the Learner Experience Cluster at Babbel and help shape the technology behind impactful, customer-facing learning experiences used by millions of learners worldwide. A Principal Software Engineer at Babbel drives outsized, durable impact across multiple teams by shaping technical direction, improving system-level outcomes, and scaling the effectiveness of others. This is a role defined by influence, planning, and strong role modeling — not authority or heroics.
Job Responsibility:
Drive architectural coherence and technical direction across multiple customer-facing systems and teams
Design and evolve high-leverage APIs, data models, and distributed systems that power learner journeys, personalization, and experimentation
Establish shared patterns, abstractions, and standards that reduce fragmentation and increase engineering leverage
Act as a role model for AI-native workflows across design, coding, testing, code review, debugging, and incident response
Champion effective and responsible usage of AI-assisted development tools and scalable prompting practices
Identify and implement opportunities where AI can measurably improve developer productivity, delivery speed, and production quality
Define guardrails and evaluation approaches to ensure AI usage is secure, reliable, and aligned with engineering standards
Improve delivery performance by advancing continuous delivery, observability, and production excellence practices
Anticipate cross-team risks and dependencies early and proactively de-risk them to protect learner experience and commitments
Multiply your impact through mentoring senior engineers, influencing without authority, and stepping in hands-on when critical paths require it
Requirements:
Extensive experience designing, building, and operating distributed systems using Typescript and AWS
Deep expertise in APIs, asynchronous systems, data modeling, and service-to-service communication in production environments
Strong architectural judgment and the ability to communicate trade-offs clearly in service of product and learner outcomes
Proven ability to improve system-level outcomes such as reliability, scalability, delivery speed, and operational excellence
Hands-on fluency with AI-assisted development tools and demonstrated integration of AI into daily engineering workflows
Experience experimenting with or building AI-powered systems, LLM integrations, or AI-enabled features
Pragmatic, metrics-driven judgment in evaluating where AI adds meaningful value versus where traditional approaches are superior
A track record of influencing technical direction across multiple teams without relying on formal authority
Strong product mindset with experience connecting technical decisions to experimentation and measurable customer impact
Demonstrated ability to mentor senior engineers, raise technical standards, and elevate AI fluency across an organization
Ability to work in English
Nice to have:
Experience with LLM evaluation frameworks, prompt engineering at scale, retrieval-augmented generation (RAG), or model experimentation pipelines
Experience building or scaling learning platforms, personalization systems, or A/B experimentation frameworks
Exposure to domain-driven design, event-driven architectures, or platform engineering
Experience shaping engineering operating models or standards during periods of technological transformation
Genuine interest in how AI, product, and learning science can combine to create meaningful learner outcomes
Experience with Golang
What we offer:
30 vacation days
3-month Sabbatical
Family and life situation counseling
Flexible working hours and remote-friendly options
Jobbatical (up to 3 months inside the EU and UK)
Fully equipped office with nap, faith and family rooms
Internal learning opportunities
Yearly learning & development budget for external training