Sr. Backend Python Developer (AI)

Our plans in Lithuania

We’re launching a new R&D team in Vilnius, Lithuania. Two of our team members are already based in Lithuania: a Lead Engineer and a QA Engineer. In Q1, we plan to hire 3 additional engineers, bringing the team to a total of five. By the end of the year, we expect the team to grow to around 10 people, depending on business needs and progress. The team will have a dedicated office in Vilnius, with an emphasis on building a strong local culture through collaboration and team activities. The Vilnius team will work closely with the wider engineering organization, with opportunities for on-site visits and team exchanges at our Amsterdam headquarters and Barcelona hub.

Your team:

For this role you will form part of our new and independent AI division. You work in a tightly-nit team alongside 2 AI engineers, an AI Intern, a dedicated FE engineer and our Head of AI. You will be reporting and working closely with the Head of AI, CTO and Head of Product. Team culture emphasizes a high level of autonomy and trust between each member – your decisions will have a significant weight on the direction of the product.

Why this role exists

We’re building out the backend and infrastructure that powers our AI assistants and student engagement tools. We need an engineer who loves writing and scaling backend systems from the API layer down to the database and infrastructure level. Someone who can design solid APIs, data flows, and services, and then wire them up to LLMs, RAG pipelines, and experimentation frameworks.

This role is about making the backend powering our AI reliable, observable, and production-ready.

Important: this is NOT an AI/ML role. You will be working with the AI team, and interface with AI systems daily – but 95% of the work will squarely fall under the “backend development” bucket. On the other hand, in this role you will have the opportunity to experiment with the latest AI practices and directly contribute to the development of AI products.

What you’ll do:

• Build, maintain and scale backend services for AI features.
  – Implement, maintain and scale Python/FastAPI services that power our chat assistants and student-facing workflows.
  – Optimize, refactor, and stabilize essential systems across the stack. We’re transitioning from a fast-moving early startup to a high-growth scale-up – you’ll help ease our growing pains.
• Testing, observability & reliability.
  – Help improve our guardrails and observability: logging, tracing, and alerts for AI features and backend services.
  – Help debug tricky production issues and sift through the noise to identify and resolve the root causes. Note: we have a dedicated QA engineering team that is directly responsible for day-to-day QA tasks.
• Experimentation & iteration.
  – Work with AI, Product, and Design to ship experiments fast and measure their impact.
  – Propose and prototype new backend or AI capabilities that meaningfully improve our product and internal tooling.
• Startup-style ad-hoc work.
  – Jump in on bug-fixes, internal tooling, or data tasks when needed.
  – Help improve our developer experience, CI/CD, and internal docs.

Non-negotiable requirements:

• You are smart, pragmatic, and love building backend systems.
• You understand that there are two sides (https://juraj.blog/p/two-sides) to software engineering and work comfortably in both.
• You can operate both as owner and as executor. At times we need a new system designed from scratch – at others, we just need to add another API integration. You enjoy doing the grunt work (sometimes!).
• STRONG ASYNC PYTHON skills, and solid understanding of advanced python concepts and libraries such as: event loops, async generators, anyio streams, decorators, generics, etc.
• Extensive experience in MongoDB.
• Deep familiarity with the terminal, your IDE of choice, and git.
• 4+ years of experience in a Software Development position. This does not include data science, MLE, devOps, and other adjacent fields.
• Professional fluency in English (written & spoken).
• IMPORTANT: the list above are deal-breakers for which we test early in the interview process. We cannot and will not compromise on these.

Important, but with some wiggle room:

• Experience with FastAPI (or similar modern web frameworks)
• Solid experience designing and maintaining backend APIs and services (HTTP APIs, auth, error handling, etc.).
• Familiarity with cloud environments (e.g. AWS, GCP, Azure) and common dev tooling (Docker, CI/CD).
• A demonstrable level of mastery of AI tooling. We’re not looking for vibe coders. We expect you to know when and how to leverage AI.
• Self-driven, highly motivated, and excited about improving higher education with technology!

Nice to have:

• Frontend experience is a big plus – will change to: Front-end experience is a big plus, as you might need to run or touch some small things. We don’t expect you to create full pages/designs, just navigate around. We have dedicated Front-End (React/ Next.js) Engineers to work with complex FE solutions.
• Experience shipping LLM-based features to production (chat, RAG, agents, tools).
• Worked with vector stores, embeddings, and retrieval (e.g. for search or question-answering).
• Exposure to observability tooling (metrics, tracing, logging stacks – in particular logfire and/or opentelemetry).
• Prior experience in a high-growth startup or small, fast-moving product team.

How we work

• Open, asynchronous communication: all communication happens in public channels by default. We have very few meetings and rely on async communication.
• Strong team spirit: we’re a team full of fantastic humans. Everyone at LearnWise loves and cares deeply about what they’re doing. If you’ve only worked at corporate jobs, the experience can be overwhelming 😉
• Small team, big ownership: you’ll own features and systems end-to-end. We don’t hold hands or micromanage. We make sure everyone has the support they need to thrive and deliver their best.
• Quality and speed: “good enough” is often better than perfect. Delivering real value to our customers is often more important than pristine coding practices. We do have refactor-parties sometimes 🙂

Location & schedule

• Full-time role in Lithuania with an opportunity to go to the office.
• Remote is OK.
• Flexible schedule and a “no strict 9–5” mentality, with real respect for work–life balance.

Compensation & benefits

• Competitive salary: €5,000–€6,500 gross.
• Flexible working arrangements, including remote work within Europe.
• An office in Vilnius for those who don’t want a fully remote setup.
• Focus on work–life balance, not clock-watching.
• Opportunity to build cutting-edge AI technology and make a real impact in EdTech.
• Join team meet-ups globally (e.g. our offsites like Costa Brava).
• Comprehensive health insurance package.
• Annual learning & development budget.
• Home office setup stipend.

Hiring process

• Intro chat (15–20 min): quick conversation with our Head of AI or CTO to learn more about you and the role.
  Technical deep dive (30–45 min): architecture & systems discussion, plus how you’d approach a backend+AI problem at LearnWise.
• Practical exercise or pairing session (45–60 min): focused on backend/API design and integrating an AI/RAG component.
• Culture/leadership chat (30 min): meet another founder or leader to ensure mutual fit.
• Offer.

Questions we would like to discuss with you:

1. How many years of experience do you have in professional software engineering (not including data science, MLE, DevOps, or adjacent roles)?
2. How many years of experience do you have with:
   – Async Python development
   – MongoDB
   – Building and maintaining production backend services (APIs, auth, error handling, observability)
3. Have you built and deployed a production-grade backend service using Python (FastAPI or similar)?
4. How comfortable are you with advanced Python concepts (decorators, generics, typing, AnyIO, streaming, async context managers)?
5. How comfortable are you with backend reliability and observability (logging, tracing, monitoring, debugging production issues)?
6. Do you have experience with cloud environments and engineering tooling (AWS/GCP/Azure, Docker, CI/CD, Git)?
7. Have you integrated backend services with AI systems (LLMs, vector DBs, RAG pipelines, AI APIs, or similar)?