51 Platform Engineer jobs in Poland available for remote work from home. Apply for positions such as Platform Engineer, Platform Engineer, Platform Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will operate and improve AWS infrastructure, including networking, compute, and databases, while managing Terraform codebases and EKS clusters. Additionally, you will participate in on-call rotations, automate operational tasks, and collaborate with development teams to ensure platform reliability and security.
Configure and maintain Azure platform services and REST API integrations to support modern integration solutions. Implement monitoring, logging, and automation scripts while creating operational documentation aligned with ITIL practices.
Design, implement, and maintain the Global AI Platform to ensure secure, scalable, and reliable access to AI capabilities. This includes managing infrastructure as code, CI/CD pipelines, and collaborating with stakeholders to onboard AI use cases.
![Software Mind is hiring for remote [C3F] Data Platform Engineer](/assets/2083550c-5c59-4fae-b76e-a23e4817e5f2.jpeg){kind=small}
You will build and operate change-data-capture pipelines from PostgreSQL into Azure using Kafka Connect and Debezium. Additionally, you will manage platform infrastructure as code and ensure data protection requirements are applied to sensitive data streams.
Lead the design and evolution of platform capabilities and engineering standards while creating reusable infrastructure patterns. Collaborate with cross-functional teams to drive automation, self-service capabilities, and platform reliability.
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You will design and maintain internal tooling and CI/CD pipelines to simplify infrastructure and improve developer productivity. Additionally, you will operate AWS infrastructure and apply SRE principles to ensure system reliability, security, and observability.
The AI Platform Engineer will build the platform, tooling, and practices to enable teams to deploy AI capabilities safely and effectively. They will integrate AI into the software development lifecycle and ensure the operational health and observability of AI systems in production.
You will design and develop tools to standardize and automate data platform operations while building internal CLI tools and data product templates. Additionally, you will implement Agentic AI workflows, maintain Apache Airflow platforms, and contribute to infrastructure-as-code and GitOps initiatives.
You will design and implement scalable data platform architectures while managing cloud infrastructure using Infrastructure as Code. Additionally, you will lead migration efforts and collaborate with cross-functional teams to ensure platform reliability, security, and performance.
The role involves creating infrastructure standards and templates, managing observability stacks, and supporting Data Engineering and AI infrastructure. You will also be responsible for SRE practices, CI/CD optimization, and managing network infrastructure in darkstores.
Build and maintain core platform components including SSO, networking, and CI/CD pipelines while managing AWS landing zones and container clusters. Design platform 'golden paths' and provide self-service tools to enable fast and secure deployments for distributed teams.
Build and maintain core platform components including SSO, networking, and CI/CD pipelines while managing AWS landing zones and container orchestration. Design platform 'golden paths' and provide self-service tools to enable fast, secure deployments for distributed teams.
Design and develop applications in Power Apps and create automated workflows using Power Automate. Manage data models in Dataverse and utilize SharePoint as a data source while collaborating on system integrations.
Lead the development and specification of technical areas such as deployment, monitoring, databases, and load balancing. Coordinate a project team of 3-4 people while ensuring the reliability and scalability of built solutions.
Assist in the deployment, configuration, and maintenance of the LigaData Big Data platform across cloud and on-premise environments. Develop automation scripts and CI/CD pipelines to streamline operational tasks and improve platform reliability.
The role involves the administration, operation, and tuning of distributed messaging platforms like Kafka and RabbitMQ. It also includes managing Apache Spark workloads and implementing governance, security, and monitoring practices for data environments.
Lead the engineering of repeatable public cloud services and solutions while defining technical standards for scalability and security. Drive the deployment of automated infrastructure using IaC and provide subject matter expertise to pre-sales and operations teams.
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Implement and maintain a cloud-native metadata management platform and data quality environment on AWS. Automate metadata ingestion, data lineage, and quality monitoring while collaborating with governance and engineering teams to drive data standards.
Own and operate the production system end-to-end, focusing on automating manual work and designing a scaling roadmap. Establish CI/CD pipelines, observability stacks, and infrastructure-as-code to ensure system reproducibility.
You will build foundational capabilities for agentic experiences, enabling AI agents to securely discover data and execute reliable workflows at enterprise scale. Additionally, you will design high-throughput systems, mentor other engineers, and contribute to technical strategy while leveraging AI-assisted engineering tools.
You will architect and own the end-to-end reliability of the Command|Alert platform, ensuring high-fidelity alert generation and effective correlation of diverse telemetry data. Additionally, you will mentor engineering teams and drive strategic technical decisions to scale the alerting engine.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to operational automation.
Design, build, and maintain backend systems and APIs for the Wikidata Query Service to ensure scalability and reliability. Monitor production systems, resolve operational bottlenecks, and contribute to deployment automation and CI/CD workflows.
Design and maintain backend systems and APIs for the Wikidata Query Service to ensure high scalability and reliability. Collaborate with SRE and product teams to monitor production systems and implement automation for data pipelines.
Manage AWS infrastructure, architecture, and security while designing CI/CD pipelines for fast, automated production deployments. Collaborate directly with stakeholders to influence product direction and integrate AI tools to optimize development workflows.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents and contribute to improvements in monitoring, automation, and operational processes.
We watch for new "Platform Engineer" jobs and email you the matches. Free. Unsubscribe in one click.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
Operate and support large-scale AI infrastructure platforms powered by NVIDIA GPUs and Kubernetes across multiple datacenters. Resolve technical incidents related to hardware, networking, and platform stability while contributing to automation and observability improvements.
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