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Senior DevOps Engineer maintaining CI/CD pipelines and building monitoring and automation capabilities for an AWS-hosted managed services platform in a financially regulated environment.
The DevOps Engineer will design and maintain multi-stage CI/CD pipelines, manage infrastructure as code using Terraform, and operate cloud environments on AWS and GCP. The role focuses on ensuring system reliability, security, and observability while leveraging AI tools to automate operational tasks and support healthcare-focused software solutions.
Build and refine CI/CD pipelines and Kubernetes-based infrastructure for Toss Securities, focusing on developer experience and robust monitoring to enable rapid, safe deployments.
Build and maintain Kubernetes-based cloud-native platforms to enable fast, safe deployments and resilient operations for Toss’s offline payment ecosystem.
Build and maintain cloud-native infrastructure on AWS EKS to enable fast, secure deployments for insurance products using Kubernetes, Terraform, and observability tools.
Build and operate ML/LLM platforms for a Korean neobank, focusing on stable, scalable, and secure model training, deployment, and serving using tools like MLflow, Kubeflow, Triton, and vLLM.
Build and maintain the core server platform for Toss’s fintech services using Java/Kotlin and Spring, focusing on scalability, monitoring, and distributed systems.
Builds and operates high-availability platform services for Toss Bank, including messaging, API gateways, monitoring, and caching, using Kotlin/Java and Spring ecosystems.
Designs and develops high-availability, scalable server systems for Toss’s offline payment solutions, focusing on system architecture, real-time traffic handling, and end-to-end service reliability using Java/Kotlin, Spring, Kafka, and cloud-native tools.
Builds and maintains scalable, secure banking services using Kotlin/Java and Spring, focusing on high-traffic systems and innovative fintech products in a collaborative squad model.
Maintains and scales Toss’s payment and financial services infrastructure to ensure high availability and performance using cloud-native tools and DevOps practices.
Builds and maintains a global financial data platform for securities, processing real-time market data with AI/ML pipelines using Kafka, Spark, and Iceberg.
Build and maintain monitoring, observability, and performance-testing systems to keep Toss Bank’s high-traffic services stable and scalable using Kotlin/Java, Kubernetes, Istio, Kafka, and Prometheus.
DevOps Engineer building and optimizing Kubernetes-based environments with GitOps (ArgoCD, GitHub Actions), implementing a full observability stack and security practices for a healthtech transformation project in hybrid Warsaw.
DevOps Engineer at LUX MED (healthcare) in Warsaw, optimizing Kubernetes clusters, building CI/CD pipelines with GitHub Actions and ArgoCD, implementing observability (Grafana, Prometheus, OpenTelemetry, ELK), managing IaC via Terraform, and enforcing security practices.
This role involves designing and maintaining enterprise-grade observability platforms using tools like Prometheus, Grafana, and OpenTelemetry to ensure system reliability. The engineer will work across cloud-native environments, focusing on metrics, logs, traces, and automation to improve incident detection and troubleshooting.
Build and operate ZoomInfo’s self-hosted CI/CD platform on GKE and Jenkins, using GitHub Actions, ArgoCD, Helm, and Terraform to deliver reliable, scalable pipelines and developer tooling.
Basic Qualifications Requires a Bachelor’s degree in Software Engineering, or a related Science, Engineering, Technology or Mathematics field. Also requires 5+ years of job-related experience, or a Master's degree…
DevOps data engineer in the Police's Business Intelligence product line in Zwolle, designing, developing, and implementing data pipelines and software solutions using Java, Python, Kubernetes, and related tools in an Agile/Scrum team.
Scale-up Full-Stack DevOps Consultant working on clean Python code, scalable cloud setups, and AI automation. Core technologies include Python, FastAPI, Kubernetes, Google Cloud Platform, and various DevOps tools for architecture design and implementation.
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