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.