AI Engineer — Build Adaptive Learning with LLMs

Uniplay

Stockholms kommun

On-site

SEK 1,000,000 - 1,300,000

Full time

14 days+
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Benefits offered by this job

Stockholm-based
Autonomy in how you work
Direct collaboration with AI experts

Job summary

Uniplay, based in Stockholm, is reshaping corporate learning with AI-powered, game-based experiences. We build an adaptive platform using real company material and data to deliver engaging learning.

We’re seeking an AI Engineer who moves from paper to prototype to production, turning research into scalable customer solutions. You will own end-to-end AI pipelines, work with messy knowledge sources, and shape our evaluation and production systems.

Qualifications

  • Real experience shipping AI systems in production environments.
  • Deep knowledge of RAG, structured generation and evals.
  • Demonstrated personal projects or open-source work.
  • Strong drive and ability to move fast.
  • Proficient in TypeScript or Python.
  • Excellent English communication; Swedish a plus.

Responsibilities

  • Build and maintain AI learning pipelines end to end.
  • Work with real knowledge sources to create adaptive content.
  • Develop evaluation infrastructure for generated content.
  • Improve AI production systems: prompts, tooling, latency and cost.
  • Influence the product roadmap and collaborate cross-functionally.
  • Review peers' work and share learnings across teams.

Skills

Real experience shipping AI systems
Depth in modern stack
Own projects
Extreme drive
Fast iteration
Strong engineering
Curiosity about learning
Team player
Clear communication in English

Tools

TypeScript
Python

Job description

Uniplay, based in Stockholm, is reshaping corporate learning with AI-powered, game-based experiences. We build an adaptive platform using real company material and data to deliver engaging learning.

We’re seeking an AI Engineer who moves from paper to prototype to production, turning research into scalable customer solutions. You will own end-to-end AI pipelines, work with messy knowledge sources, and shape our evaluation and production systems.

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