Senior AI Engineer

Role

We're looking for a senior AI Engineer for a consulting assignment focused on building AI-driven capabilities in a business-critical, quality-sensitive setting for a company within healthcare/medtech.

Responsibilities

Build AI functions that turn clinical content into practical, actionable suggestions for therapists in their daily work.
Design end-to-end pipelines, including prompt and chain architectures, with structured outputs broken into clear, independently testable steps.
Own model selection and strategy, including fine-tuning open-weight models.
Help establish a data foundation with measurable quality, ensuring data is de-identified, version-controlled, and reproducible.
Define per-function evaluation methodology — identifying which error types matter most and what quality bar must be met before output reaches a human reviewer.
Set up regression testing and continuous quality monitoring in production.
Build traceability mechanisms capturing what the AI suggests versus what the reviewer approves or edits, supporting transparency and long-term improvement.

Required Skills

Proven experience building LLM-based systems that run in production, not just proof-of-concept work.
Able to give concrete examples of how you've iterated on and improved live solutions over time.
Strong background across data modeling, pipeline development, and model-related engineering.
Clear understanding of why versioning datasets matters as much as versioning code.
Experience handling sensitive personal data, with a real grasp of how nuanced de-identification can be.
Comfortable working against defined quality bars rather than optimizing for a demo.
Understands the stakes of reliability in AI systems, particularly where mistakes carry real consequences.
Consulting mindset: able to step into an existing team, collaborate closely with domain experts, and leave behind solutions others can maintain.

Nice to Have

Background in medical technology, healthcare, or other regulated fields with strong traceability requirements.
Experience with speech-to-text systems, particularly for Swedish as a lower-resource language.
Familiarity with the .NET ecosystem.