Senior AI Engineer

Role Summary

An experienced AI Engineer is needed for a consulting assignment focused on developing AI-driven capabilities in a business-critical, quality-sensitive clinical environment. The role will help transform clinical content into useful, reliable suggestions that support healthcare professionals in their daily work.

You will design and implement production-ready AI solutions with clear, testable stages, including pipelines, prompt and chain structures, and structured outputs. The assignment has a strong emphasis on measurable quality, reliability, transparency, and continuous improvement in contexts where incorrect AI responses may have significant consequences.

Key Responsibilities

• Develop and maintain production-grade LLM-based features that convert clinical content into actionable suggestions for healthcare professionals.
• Design AI pipelines, prompt structures, chaining logic, and structured outputs that can be tested independently at each stage.
• Define model selection and model strategy, including the fine-tuning of open-weight models where appropriate.
• Build a high-quality data foundation with de-identified, version-controlled, and reproducible datasets.
• Establish evaluation methodologies for each AI capability, including the definition and prioritisation of error types and release criteria before output is presented to end users.
• Implement regression testing and continuous quality monitoring for AI functionality in production.
• Create traceability for AI-generated suggestions and record whether healthcare professionals approve or modify those suggestions.
• Work closely with domain experts in an existing technical environment and deliver maintainable solutions that can be managed by internal teams over time.

Technical Stack & Requirements

• Hands-on experience building and operating LLM-based systems in production, rather than only prototypes or demonstrations.
• Strong capability in prompt engineering, multi-step AI workflows, structured output design, and model-adjacent engineering.
• Experience with model selection strategies and fine-tuning of open-weight language models.
• Strong knowledge of data modelling, data pipelines, dataset versioning, and reproducible AI development workflows.
• Experience establishing AI evaluation methods, regression tests, production monitoring, and quality follow-up.
• Ability to handle sensitive personal data and implement robust de-identification practices.
• Experience in a .NET environment is advantageous.
• Experience with speech-to-text technology and Swedish as a low-resource language is advantageous.

Qualifications & Experience

You should be a senior-level AI engineer with demonstrated experience iterating on, improving, and operating AI solutions over time. You are expected to understand why dataset versioning is as important as source-code versioning and to be comfortable working against explicit quality requirements rather than focusing solely on demonstrable output.

Experience from medical technology, healthcare, or another regulated environment with high traceability requirements is beneficial. The ideal consultant is accustomed to joining established delivery environments, collaborating closely with subject-matter experts, and creating sustainable solutions for long-term ownership.

Interested? Please share your updated CV at cv@veritaz.se to proceed further.