Key skills
AILLMCommunication
About this role
Role Overview
- You'll build and operate the shared AI capabilities behind Aidn's digital colleague direction.
- Creating the reusable components, APIs, evaluation patterns, and tooling that let other product teams adopt AI safely, without reinventing core infrastructure.
- Taking capabilities like speech-to-summary, form-filling, and contextual drafting from pilot to production, tied to the correct patient, case, and data context, with real attention to latency, cost, reliability, and failure modes.
- Building safe execution into the platform: previews before actions, human-in-the-loop checkpoints, risk tagging, rollback, full traceability and audit trails, and the separation between MDR and non-MDR contexts.
- Establishing how we test, measure, and monitor AI behaviour over time, eval frameworks, ground-truth validation, regression detection, and production monitoring, so quality and trust hold as usage scales.
Requirements
- Strong software and systems engineering: you've built and operated production systems, with sound judgment on reliability, scalability, and maintainability.
- Shipped applied AI in production, not just prototypes: you've taken LLM
- or speech-based capabilities into real use and handled latency, cost, reliability, and failure modes.
- Built things other engineers depend on: shared services, APIs, libraries, or platform components, with the interfaces and documentation that made adoption easy.
- Evaluation and observability as a habit: you measure system behaviour and build confidence through evidence, not assumption.
- Safe-by-design engineering: comfortable building with guardrails, traceability, audit trails, human-in-the-loop checkpoints, and controlled execution.
- Strong communication and clear technical writing in English.
Benefits
- 6 weeks vacation
- Flexible location and working hours
- Employee shares—you can own a piece of what you build
- A collaborative, caring team that values both kindness and excellence