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Urgent! AI Engineering Intern (LLM Ops & RAG) Position in Vigo - LearnWise AI

AI Engineering Intern (LLM Ops & RAG)



Job description

LearnWise is a company where the best idea always wins — no matter what — and where innovation and hyper-growth are in our DNA.


We offer Engineering internships designed to build future technical leaders - hopefully at LearnWise!


Internship · EU · Remote

Department: Engineering

Reports to: Head of AI

Work alongside: CTO, AI team, Engineering & Product


Job Description

LearnWise.ai is a scale-up modernizing educational institutions with virtual assistants, instructor efficiency, and student engagement solutions for higher education.

We’re seeking an inspired and rigorous Engineering Intern for a 6-month internship focused on AI systems, reliability, and product behavior.


You’ll join a VC-funded team with a track record of exponential growth.

You’ll work closely with leadership and be expected to propose, test, and ship your own ideas.



What you’ll do

AI Systems & Reliability

  • Troubleshoot LLM behavior and agent actions across our Tutor Assistant, automatic feedback, and other AI features; identify root causes and ship fixes.

  • Use LangSmith, LogFire and other tools to trace requests end-to-end, correlate prompts, tools, and outputs, and explain why a behavior occurred.

  • Implement pragmatic guardrails, fallbacks, and caching; reduce failure modes and improve correctness under real usage.

Retrieval & Relevance

  • Optimize our retrieval pipelines: choose and tune embeddings, refine vector-database indexing/search strategies, and evaluate re-rankers for higher precision/recall.

  • Design and run experiments (e.g., , MRR, nDCG, groundedness checks) that translate directly into product wins.

LLM Ops & Tooling

  • Contribute to LLM Ops: prompt/tool versioning, dataset curation, regression test suites, latency/cost monitoring, and safe rollout strategies (shadow, A/B).

  • Build small utilities to surface failure taxonomies, detect drift, and turn traces into actionable fixes.

  • Grow into feature development that measurably improves product quality and student outcomes.

Collaboration & Strategy

  • Partner with the Head of AI, CTO, AI team, Engineering, and Product to shape technical direction.

  • Share learnings clearly; propose changes that improve model performance, reliability, and UX.
Requirements

Core Requirements

  • Strong proficiency in Python.

  • Master’s (ongoing or completed) in AI/ML or a related field, or equivalent experience demonstrating comparable depth.

  • Solid understanding of modern AI models and AI-powered applications (prompting, tool-use/agents, RAG, context management, evaluation).

  • Hands-on experience with LLMs and/or tool-using agents: debugging prompts, tracing tool calls, analyzing failure modes.

  • Ability to design evaluation loops (golden sets, regression tests, online experiments) that make reliability measurable and improvable.

  • Ability to figure things out independently and chase issues until completion.

Nice to Have

  • Experience optimizing RAG components: embeddings selection/tuning, vector DB configuration, re-ranker selection/evaluation.

  • Familiarity with AI observability/monitoring practices and failure taxonomies.

  • Fluent in English; direct, candid communication style; hungry to learn and ship.
What’s in it for you?

  • Direct mentorship from senior leadership (CTO, Head of AI, Head of Product).

  • Work with a global team on cutting-edge AI applications.

  • Flexible working arrangements (results > hours).

  • A “no 9-to-5 mentality” and genuine focus on work-life balance.


If you’re passionate about engineering with AI, eager to learn, and excited to work in a fast, practical startup environment, this is your chance to build AI that meaningfully improves student outcomes.

We’d love to hear from you.


Required Skill Profession

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