Senior Backend AI Engineer - LearnWise AI
hace 5 días
Barcelona
About LearnWise AI We’re an AI-first startup helping universities and colleges support students and faculty with smart, knowledge-driven tools. Small team, high ownership, real user impact. LearnWise is a place where the best idea wins—no matter who says it—and where innovation and growth are in our DNA. You’ll work closely with our Head of AI, CTO, and Head of Product. Why this role exists We’re building AI-powered product features that need to be reliable, useful, scalable, and shipped fast. We need an engineer who can take meaningful product areas from idea to production: understand the user problem, design the system, build the backend, integrate with LLMs and AI APIs, ship the feature, observe how it behaves, and iterate. This role sits at the intersection of backend engineering, product engineering, and applied AI systems. You’ll build APIs, services, data flows, integrations, and infrastructure—but you’ll also work directly with LLM APIs, RAG pipelines, tool-calling, agentic workflows, experimentation frameworks, and AI-specific observability. This is not primarily an AI/ML research role. You will not be training foundation models or doing academic ML. You will, however, be building production-grade systems around LLMs and AI agents, and you should be genuinely fluent in how modern AI systems are designed, called, evaluated, debugged, and shipped. What you’ll do • Own and ship AI-powered product features end-to-endTake substantial features from concept to production: clarify the problem, design the system, build it, ship it, observe it, and iterate., • Work closely with AI, Product, Design, and Engineering to turn product goals into pragmatic technical solutions., • Balance speed, quality, reliability, and user impact in real production systems., • Build backend systems for AI productsImplement, maintain, and scale Python/FastAPI services powering our chat assistants, student-facing workflows, faculty tools, and internal AI systems., • Design APIs, service boundaries, data models, integrations, and async workflows., • Refactor, stabilize, and improve core systems as we grow from early startup to scale-up., • Work deeply with LLMs, RAG, tools, and agentsIntegrate backend services with LLM APIs, vector stores, embeddings, rerankers, retrieval pipelines, and tool-calling systems., • Build robust patterns for prompts, tools, structured outputs, streaming, retries, fallbacks, guardrails, and failure handling., • Help design agentic workflows that safely and reliably interact with external systems and internal APIs., • Improve reliability, observability, and evaluationStrengthen logging, tracing, metrics, alerts, evaluations, and debugging workflows for AI features and backend services., • Debug tricky production issues and identify root causes across backend, infrastructure, and AI-system behavior., • Build systems that are inspectable, measurable, and maintainable—not black boxes., • Experiment, iterate, and jump in where neededShip experiments quickly, measure their impact, and improve based on real usage and customer feedback., • Prototype backend, product, or AI capabilities that improve the product or internal tooling., • Help with bug fixes, integrations, scripts, data tasks, CI/CD, developer experience, and internal docs when needed. Non-negotiable requirements: • You are smart, pragmatic, and love building real product 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!)., • You have strong product-engineering instincts: you can reason about what should be built, not only how to build it., • STRONG ASYNC PYTHON skills, and solid understanding of advanced python concepts and libraries such as: event loops, async generators, anyio streams, decorators, generics, etc., • Experience with FastAPI (or similar modern Python web frameworks)., • Extensive experience in MongoDB., • Deep familiarity with the terminal, your IDE of choice, and git., • Strong familiarity with LLM APIs and applied AI systems, including tool-calling, structured outputs, RAG, embeddings, streaming, retries, prompt design, and failure modes., • 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: • 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, • 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., • Remote is OK; EU is a must-have., • We’re especially happy if you’re around Amsterdam or open to occasional in-person meet-ups., • Flexible schedule and a “no strict 9–5” mentality, with real respect for work–life balance. Compensation & benefits • Competitive salary., • Flexible working arrangements, including remote work within Europe., • 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). 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 Interview (45-60 min): technical knowledge questions, • 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.
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