Assignment description
Our client is seeking an LLM/ML Engineer to integrate AI more deeply into their platform. You’ll play a key role in shaping developer workflows, infrastructure, and knowledge graph initiatives that power the future of AI-driven learning.

What You’ll Do:
– Set up AI/LLM workflows: create a robust, scalable developer environment with CI/CD and DevOps best practices.
– Review and optimize infrastructure to ensure scalability, reliability, and cost-efficiency for AI use cases.
– Work with LLMs and AI SDKs to design context engineering pipelines and integrate AI agents.
– Contribute to building a knowledge graph that supports personalized, adaptive learning experiences.
– Collaborate closely with a small dev team (Next.js, TypeScript, PostgreSQL, AWS) to integrate AI into the product.

About the team
The team consists of 1,5 fulltime developers as of today

Must haves
– Deep expertise in LLMs and applied AI (context handling, SDKs, agent workflows).
– Strong background in ML engineering, DevOps, and CI/CD.
– Experience designing developer productivity workflows (Codex, CloudCode, or similar).
– Ability to work independently and take ownership in a small, fast-moving team.

Other requirements
Nice-to-Have:
– Hands-on experience with Next.js, TypeScript, PostgreSQL, AWS.
– Previous work in edtech or knowledge delivery platforms.
– Experience with API integrations and large-scale data validation.

About the customer
Our client helps engineering students with their studies. Their platform transforms static academic content into engaging, interactive experiences. Their mission is to boost student success and retention in STEM fields by giving students what they need.