Help us create the software platform that will change Norwegian healthcare forever.
Location: Oslo, Bergen, Bodø, Stavanger, or from anywhere in Norway
Salary: 1.2-1.3 MNOK/year
Somewhere in Norway right now, a nurse is filling in a form instead of caring for someone. As municipalities face growing pressure to deliver more care with fewer resources, time saved in daily work has become one of the most valuable things we can deliver.
At Aidn, we’re creating the missing healthcare platform all Norwegians deserve: an integrated set of services and applications that allow municipal institutions, healthcare professionals, social workers, and citizens to collaborate on healthcare matters as a single team. We're building toward a future where healthcare staff have an always-available digital colleague: one that surfaces the right information at the right time, cuts repetitive admin tasks and supports better decisions.
As a Senior AI Engineer, you'll build and operate the AI platform the rest of Aidn runs on, the production services, guardrails, and shared components that other teams use to build their own AI features.
The distance between AI that's impressive in a demo and AI a clinician will trust on a shift is real. Closing that gap, by making it reliable, observable, and safe enough for healthcare, is the job. Getting it right means a nurse gets her afternoon back. Getting it right at scale, across every municipality we serve, means thousands of hours returned to patient care, and Norway a step closer to a healthcare system that helps people live the longest, healthiest lives possible.
You'll build and operate the shared AI capabilities behind Aidn's digital colleague direction. The work sits where applied AI, safe automation, and platform engineering meet, and it's measured in real time returned to patient care.
Your work will include things like:
Shared AI building blocks: Creating the reusable components, APIs, evaluation patterns, and tooling that let other product teams adopt AI safely, without reinventing core infrastructure. This is the heart of the role.
Applied AI into production: 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.
Guardrails for healthcare: 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.
Evaluation and observability: 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.
Agentic and multi-step flows: Helping shape controlled, goal-driven automation, proposing and chaining steps like preparing a case or drafting a letter, with strict safety boundaries. This is emerging work as the platform matures.
We build on modern, production-proven technology, chosen for reliability, traceability, and safe execution in healthcare. The result is AI that teams and municipalities can actually trust.
We use:
Languages & frameworks: Python for AI platform and evaluation tooling, C# / .NET for core backend services.
Cloud & AI platform: Microsoft Azure, including Azure AI services and Azure AI Foundry
Data & storage: PostgreSQL and Azure Storage
Messaging & streaming: Azure Event Hub (Kafka)
Infrastructure & CI/CD: GitHub Actions, ArgoCD, Terraform
Observability: LGTM stack (Loki, Grafana, Tempo, and Mimir)
You don't need every item on this list. You should be comfortable working across a stack like this and confident picking up what you don't already know. We care more about how you think than exactly what you've used.
A hands-on engineer who pairs strong software and systems fundamentals with real experience shipping AI in production. You care about capabilities that are safe, observable, and reusable, not just impressive demos.
Must-Haves
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.
Nice-to-Haves
Building agentic systems or multi-step AI workflows
Operating AI in production: quality, cost, latency, drift, failure modes
Azure / Azure AI Foundry or similar model deployment and governance tooling
Regulated environments where traceability and auditability are non-negotiable
Workflow orchestration, state machines, or event-driven architectures
Experience or contributions to open source software
Who thrives here
The people who do well in this role are pragmatic rather than perfectionist, they ship the thinnest safe slice that delivers value, then improve it. They have high agency and move work forward even when the path isn't fully drawn. They're drawn to problems where reliability, scale, and real healthcare constraints make the engineering genuinely hard, and they get as much satisfaction from helping another team ship safely as from their own code. Honest, direct, and good to work alongside.
You're productive in the codebase and have shipped real improvements to the platform or its production services.
You understand the AI platform, its guardrails, and the healthcare constraints that shape it (traceability, audit, human-in-the-loop, MDR separation).
You've built trust across Team Automation and key partner teams as a pragmatic engineer who moves work forward.
You're independently delivering production-grade platform capabilities used in real workflows.
You've helped at least one other team adopt the platform for a real use case, beyond prototypes.
You've strengthened evaluation and monitoring so the team can catch regressions and trust production behaviour.
A capability you helped productionise, such as speech-to-summary or form-filling, is running in production with credible evidence of time saved.
Multiple teams are building on the shared platform using your patterns and components, with little hand-holding.
Aidn has a more mature, scalable foundation for AI: clearer evaluation standards, better observability, and more consistent practices across teams.
You’ll be trusted to make decisions, take initiative, and shape your own path. There’s little bureaucracy, and we hire people we trust to figure things out.
You’ll be joining a growing Platform organization at a pivotal stage, with the chance to leave a real mark on how our backend systems evolve. As Aidn scales, your opportunities to lead, mentor, and influence technical direction will grow alongside it.
You’ll have regular 1:1s, feedback, and mentoring from experienced engineering leaders. We support personal development through learning budgets, conference access, and time for deep work.
Work from home, from one of our local offices, or take a workation if you need a change of scenery. We trust you to manage your time in a way that works for you and your team.
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
Aidn is part of the Kernel cooperation, where we build technology for the next generation of welfare societies. With financial backing in order, we are privileged to be a fully autonomous startup busy building our company from the ground up the way we see fit.
Aidn recognizes and celebrates diversity in all its forms, visible and non-visible in all areas of the work environment. We work to promote an anti-discriminatory environment where everyone feels safe and welcome.
Read our full Diversity, Inclusion & Belonging policy in our handbook here
Are you curious? We welcome you to check out our employee handbook to get to know us, some of our benefits, and what drives us.
--Recruitment for this role will start in August--
The future patient-centric e-health system. Making the complex simple.
Aidn will create an interconnected and trusted ecosystem where citizens, clinicians, and administrators can collaborate on healthcare outcomes as a unified team sharing data from a single patient journal.
Our products will grant patients unprecedented access to and control over their own data while giving healthcare workers the tools they need to spend as much of their time and energy as possible on their true calling.
Aidn is a member of the Kernel family, a collection of like-minded companies focused on building the next generation of healthcare services in Norway and beyond.
