Kaiko is building a next‑generation agentic clinical AI assistant that helps clinicians reason across patient data, guidelines, and diagnostics.
Healthcare decisions are rarely made by a single person or from a single data source. Kaiko's assistant maintains longitudinal patient context across encounters, clinicians, and institutions, enabling collaboration, second opinions, and complex diagnostic workflows. The system is designed to operate safely in real clinical environments, with human oversight, auditability, and regulatory alignment at its core.
Our assistant core supports broadly applicable clinical tasks such as patient data navigation, guideline interaction, multimodal interaction (chat and voice), and care coordination. On top of this foundation, we are developing specialized diagnostic agents in areas such as oncology, radiology, and pathology.
We build in close collaboration with leading hospitals and research centers, including the Netherlands Cancer Institute (NKI). kaiko is a well‑funded company with a growing international team, operating from Zurich and Amsterdam.
About The Role Our team is tackling the challenge of building a secure, scalable data and AI platform that can process massive, multimodal datasets for training cutting‑edge MLLM models while also handling sensitive medical data directly within hospital environments.
As a Data Platform Engineer, you'll design, deploy, maintain and optimize a self‑hosted, open‑source‑driven infrastructure that powers data ingestion, transformation, and serving for both AI training pipelines and real‑time hospital applications. Your primary focus will be on the platform itself – the infrastructure, tooling, and services that enable others to work with data effectively, rather than building data pipelines as an end goal. Your work will ensure that pipelines built on top of our platform are reproducible and compliant with strict privacy regulations.
This is a rare opportunity to shape a platform from the ground up – working with state‑of‑the‑art tooling, solving unique scaling and security problems, and owning key technical decisions that will directly impact groundbreaking AI models and healthcare workflows.
You will be based in either The Netherlands or Switzerland, with the expectation of spending at least 50% of your time at the office.
Some areas of responsibility
Design, maintain and own infrastructure and deployment for data exploration, transformation, and storage – including orchestration, containerization, and monitoring.
Build and maintain internal platform services that abstract away complexity and promote self‑serve data access and processing.
Manage, deploy, and champion the use of standard open‑source tooling and products around data platform and data engineering – including deploying and managing services via Helm charts and provisioning resources with Terraform.
Design and implement data pipelines where needed, contributing to data and ML workflows as part of broader platform ownership.
Collaborate with researchers, product teams, and other stakeholders to support their data needs.
About You
2‑5 years of experience in production data platform, infrastructure, or platform engineering roles.
Experience in providing in‑house data orchestration services based on open‑source software such as Dagster, Airflow or Prefect.
Hands‑on experience with infrastructure‑as‑code and container orchestration – particularly Terraform for resource provisioning and Helm for deploying services to Kubernetes.
Proficiency with modern storage formats (e.g., Parquet, Delta, Iceberg) and object stores (e.g., S3, MinIO, Azure Blob).
Solid programming skills in Python or another language suitable for data workflows (e.g., Scala or Java).
Ability to thrive in a fast‑paced, startup environment with a high degree of ownership.
Nice to have
Experience in AI/ML environment.
Understanding of data standards in the medical domain, such as DICOM, FHIR, pathology slide images (Whole Slide Images).
Experience with high‑performance (parallel) filesystems that feed GPU's with high throughput and low latency (Hammerspace, CEPH, WEKA, VAST).
Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack or Datadog).
What we value
Ownership: You’ll have the autonomy to set your own goals, make critical decisions, and see the direct impact of your work.
Collaboration: You’ll have to approach disagreement with curiosity, build on common ground and create solutions together.
Ambition: You’ll be surrounded by people who set high standards for themselves and others, who see obstacles as opportunities, and who are relentless in their work to create better outcomes for patients.
Benefits
Attractive and competitive salary, a good pension plan and 25 vacation days per year.
Great off‑sites and team events to strengthen the team and celebrate successes together.
A EUR 1,000 learning and development budget to help you grow.
Autonomy to do your work the way that works best for you, whether you have a kid or prefer early mornings.
An annual commuting subsidy.
#J-18808-Ljbffr
Healthcare decisions are rarely made by a single person or from a single data source. Kaiko's assistant maintains longitudinal patient context across encounters, clinicians, and institutions, enabling collaboration, second opinions, and complex diagnostic workflows. The system is designed to operate safely in real clinical environments, with human oversight, auditability, and regulatory alignment at its core.
Our assistant core supports broadly applicable clinical tasks such as patient data navigation, guideline interaction, multimodal interaction (chat and voice), and care coordination. On top of this foundation, we are developing specialized diagnostic agents in areas such as oncology, radiology, and pathology.
We build in close collaboration with leading hospitals and research centers, including the Netherlands Cancer Institute (NKI). kaiko is a well‑funded company with a growing international team, operating from Zurich and Amsterdam.
About The Role Our team is tackling the challenge of building a secure, scalable data and AI platform that can process massive, multimodal datasets for training cutting‑edge MLLM models while also handling sensitive medical data directly within hospital environments.
As a Data Platform Engineer, you'll design, deploy, maintain and optimize a self‑hosted, open‑source‑driven infrastructure that powers data ingestion, transformation, and serving for both AI training pipelines and real‑time hospital applications. Your primary focus will be on the platform itself – the infrastructure, tooling, and services that enable others to work with data effectively, rather than building data pipelines as an end goal. Your work will ensure that pipelines built on top of our platform are reproducible and compliant with strict privacy regulations.
This is a rare opportunity to shape a platform from the ground up – working with state‑of‑the‑art tooling, solving unique scaling and security problems, and owning key technical decisions that will directly impact groundbreaking AI models and healthcare workflows.
You will be based in either The Netherlands or Switzerland, with the expectation of spending at least 50% of your time at the office.
Some areas of responsibility
Design, maintain and own infrastructure and deployment for data exploration, transformation, and storage – including orchestration, containerization, and monitoring.
Build and maintain internal platform services that abstract away complexity and promote self‑serve data access and processing.
Manage, deploy, and champion the use of standard open‑source tooling and products around data platform and data engineering – including deploying and managing services via Helm charts and provisioning resources with Terraform.
Design and implement data pipelines where needed, contributing to data and ML workflows as part of broader platform ownership.
Collaborate with researchers, product teams, and other stakeholders to support their data needs.
About You
2‑5 years of experience in production data platform, infrastructure, or platform engineering roles.
Experience in providing in‑house data orchestration services based on open‑source software such as Dagster, Airflow or Prefect.
Hands‑on experience with infrastructure‑as‑code and container orchestration – particularly Terraform for resource provisioning and Helm for deploying services to Kubernetes.
Proficiency with modern storage formats (e.g., Parquet, Delta, Iceberg) and object stores (e.g., S3, MinIO, Azure Blob).
Solid programming skills in Python or another language suitable for data workflows (e.g., Scala or Java).
Ability to thrive in a fast‑paced, startup environment with a high degree of ownership.
Nice to have
Experience in AI/ML environment.
Understanding of data standards in the medical domain, such as DICOM, FHIR, pathology slide images (Whole Slide Images).
Experience with high‑performance (parallel) filesystems that feed GPU's with high throughput and low latency (Hammerspace, CEPH, WEKA, VAST).
Knowledge of monitoring, logging, alerting and observability tools (Prometheus, Grafana, ELK Stack or Datadog).
What we value
Ownership: You’ll have the autonomy to set your own goals, make critical decisions, and see the direct impact of your work.
Collaboration: You’ll have to approach disagreement with curiosity, build on common ground and create solutions together.
Ambition: You’ll be surrounded by people who set high standards for themselves and others, who see obstacles as opportunities, and who are relentless in their work to create better outcomes for patients.
Benefits
Attractive and competitive salary, a good pension plan and 25 vacation days per year.
Great off‑sites and team events to strengthen the team and celebrate successes together.
A EUR 1,000 learning and development budget to help you grow.
Autonomy to do your work the way that works best for you, whether you have a kid or prefer early mornings.
An annual commuting subsidy.
#J-18808-Ljbffr
Data Platform Engineer Arbeitgeber: kaiko.ai
Kaiko.ai in Zürich ist ein hervorragender Arbeitgeber, der eine dynamische und innovative Arbeitsumgebung bietet, in der Mitarbeiter die Möglichkeit haben, an bedeutenden Projekten im Bereich der Gesundheitsdaten und KI zu arbeiten. Mit einem wettbewerbsfähigen Gehalt, einem Lernbudget und 25 Urlaubstagen jährlich fördert das Unternehmen die persönliche und berufliche Weiterentwicklung seiner Mitarbeiter und schafft eine Kultur des kontinuierlichen Lernens und der Zusammenarbeit.
