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Job Overview
Location
Copenhagen
Job Type
Full-time
Category
Software Engineering
Date Posted
November 21, 2025
Full Job Description
đź“‹ Description
- • Own and evolve Corti’s self-hosted observability stack running on multi-tenant Kubernetes clusters, ensuring every heartbeat of our AI platform is visible, trustworthy, and actionable.
- • Lead the design, deployment, and day-2 operations of the LGTM stack (Loki, Grafana, Tempo, Mimir) at petabyte scale, turning raw logs, traces, and metrics into the single pane of glass that keeps our life-critical services healthy.
- • Reduce MTTR and RTO by architecting signal-to-noise-optimized alerting, intelligent correlation, and automated runbooks that let on-call engineers resolve incidents in minutes, not hours.
- • Build reusable Golang and Python libraries that standardize structured logging, distributed tracing, and RED/USE metrics across dozens of microservices, eliminating observability drift and freeing product teams to focus on patient impact.
- • Champion SLOs and SLIs as first-class citizens: define error budgets, burn-rate alerts, and quarterly reliability reviews that align engineering velocity with patient safety and regulatory trust.
- • Design cost-aware retention and tiering strategies that balance compliance (GDPR, HIPAA) with cloud spend, ensuring we never lose the data that trains tomorrow’s life-saving models.
- • Create golden-path developer tooling—local observability sandboxes, one-click trace sampling, and CI-driven performance regression gates—that cuts debugging time and accelerates feature delivery.
- • Implement GitOps-driven Kubernetes Operators for deploying stateful workloads such as PostgreSQL, Redis, and Kafka, guaranteeing zero-downtime upgrades and automated failover for the data pipelines that power Corti’s real-time medical reasoning.
- • Collaborate with security and compliance teams to embed RBAC, audit logging, and anomaly detection into every layer of the stack, meeting ISO 27001 and SOC 2 controls without slowing release cadence.
- • Mentor engineers across backend, data, and ML teams on observability best practices, running internal workshops and brown-bags that raise the reliability bar company-wide.
- • Contribute to open-source initiatives (Grafana Agent, Prometheus, OpenTelemetry) to give back to the community and influence the standards that will shape the next decade of healthcare observability.
- • Work in a hybrid Copenhagen setup—three days in our waterfront office, two days wherever you focus best—while staying fully integrated through Slack, Zoom, and Miro rituals that keep a global team in sync.
🎯 Requirements
- • 5+ years in a Senior Platform, DevOps, or SRE role building and running observability at scale on Kubernetes.
- • Production mastery of the LGTM stack (Loki, Grafana, Tempo, Mimir) including multi-tenant configuration, high-availability, and performance tuning.
- • Expert-level coding skills in Golang or Python with a track record of shipping libraries and CLIs used by other engineers.
- • Deep understanding of SLOs, SLIs, error budgets, and alert fatigue mitigation strategies.
- • Hands-on experience with Infrastructure-as-Code (Terraform, Pulumi, or Crossplane) on Azure, AWS, or GCP.
- • Nice-to-have: contributions to open-source observability projects or speaking at KubeCon, PromCon, or equivalent.
🏖️ Benefits
- • Hybrid working model with a bright, waterfront Copenhagen office and flexible home days.
- • Top-tier hardware and home-office stipend—choose your laptop, monitors, and peripherals.
- • 30 days paid vacation plus Danish public holidays and an extra week off between Christmas and New Year.
- • Comprehensive private health insurance and access to mental-health support platforms.
- • Annual learning budget (courses, conferences, books) and dedicated 10% innovation time for personal projects.
Skills & Technologies
Python
Go
PostgreSQL
Redis
AWS
Senior
Remote
About Corti ApS
Copenhagen-based Corti ApS builds machine-learning software that analyzes patient-provider conversations in real time to detect critical conditions such as cardiac arrest, flag documentation gaps, and suggest next steps during emergency calls and telehealth consultations. The platform integrates with existing dispatch and electronic health-record systems, helping clinicians reduce diagnostic errors, speed response times, and automate administrative tasks through natural-language processing and evidence-based clinical guidelines.
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