Job Description
At LearnWorlds, we believe learning is the original human superpower — the force that turns knowledge into products, skills, and progress.
Our platform helps creators, educators, and organizations in more than 150 countries turn expertise into scalable learning experiences that sell, teach, and transform. As AI floods the world with information, learning becomes the only countermeasure — the skill that keeps humans creative, relevant, and in control. The winners won’t be those who automate fastest, but those who learn and adapt fastest. They’ll need platforms that turn knowledge into teachable systems that scale — and that’s exactly what LearnWorlds enables. Build. Ship. Learn. Improve. (Repeat.)
We’re redefining how people create and share online learning—and we’re doing it with engineers who care deeply about product quality, clean architecture, and meaningful impact.
We’re a remote-first, fast-growing EdTech SaaS with a global footprint. Our Engineering team builds the core experiences that thousands of educators and learners rely on daily. We move fast, we collaborate tightly, and we’re constantly leveling up—both as individuals and as a team.
We are now looking for an AI Engineer to design, build, and scale production-grade AI systems across our platform. This role focuses on LLM-backed services, retrieval systems, prompts, and evaluation pipelines that power real product features.
If you are an engineer who wants to work on real AI systems used at scale, this is where your work will matter.
What You’ll Be Doing
- Design and ship LLM-powered backend systems that support real product features
- Build and maintain retrieval-augmented generation pipelines, including chunking, embeddings, and retrieval logic
- Develop and evolve backend services that integrate LLM workflows into a large-scale SaaS platform
- Work with document, structured data stores, and vector databases to support AI-driven retrieval and experimentation
- Design, version, and maintain prompt pipelines that are reliable, testable, and production-ready
- Build evaluation and monitoring systems to track quality, latency, cost, and regressions
- Collaborate closely with frontend engineers to ship end-to-end AI features
- Participate in deep, structured code reviews and help define standards for AI engineering
- Use AI-powered coding tools to accelerate development, exploration, and testing
Why You’ll Love This Role
- You’ll work on real AI-powered features used by thousands of educators and tens of millions of learners worldwide.
- You’ll build and improve production LLM systems that directly impact how learning content is created, structured, and consumed.
- You’ll collaborate across backend and frontend teams to ship AI features end to end.
- You’ll be part of a tight-knit team where your ideas matter and your work reaches production fast.
- You’ll grow fast, technically and professionally, in a team that values learning, clarity, and collaboration.
You’ll Thrive Here If You…
- Prefer ownership over hand-holding and clarity over bureaucracy.
- Believe speed and quality can, and should, co-exist.
- Ask “why” before “how,” especially when designing AI systems and tradeoffs.
- Treat prompts, retrieval, and evals as engineering problems, not hacks.
- Care about clean code, sound architecture, and continuous improvement.
- Embrace feedback, stay curious, and enjoy sharing knowledge.
- Believe AI will not replace engineers, but it will amplify the best ones.
Must-haves
- 6+ years of professional experience as a software engineer.
- Proven experience building and operating LLM-powered systems in production.
- Strong software engineering fundamentals, APIs, data modeling, performance, reliability.
- Hands-on experience with RAG architectures, embeddings, chunking, retrieval, and reranking.
- Experience working with vector databases alongside document and structured data stores.
- Experience designing, maintaining, and iterating on prompts for production systems.
- Experience building or using evaluation frameworks for quality, cost, and latency.
- Strong debugging, problem-solving, and systems-thinking skills.
- High attention to detail and a product-oriented mindset.
- Native or near-native Greek speaker.
Nice-to-haves
Experience operating AI systems in production environments.
Exposure to any of PHP, Go, Python, and JavaScript in real-world systems.
Familiarity with PostgreSQL (including pgvector) and MongoDB.
Experience with vector search and hybrid retrieval setups.
Familiarity with Docker, Kubernetes, or microservices architectures.
Frontend experience or strong collaboration with frontend teams is considered a plus.
Experience in EdTech, LMS platforms, or other complex SaaS products.
GitHub repositories, open-source contributions, or personal projects you are proud of.
Private life and health insurance plan
Fully remote work if you prefer to work from home, apart from when we have team meetings a few times per year
Your personal annual training budget
An annual home office allowance to set up your personal space
Company laptop & monitor
23 days of paid time off
3 early summer Fridays in July and August
A free LearnWorlds School to build and sell your own courses
Work in one of the globally top 5 e-learning courses platform
An opportunity to grow alongside us and shape the look and feel of tomorrow’s e-learning
An entrepreneurial, international, and highly motivated team with a flat hierarchy that will both challenge you and help you reach your highest potential
Annual company retreats (see the video of our latest retreat).
