53 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 improve developer experience and engineering productivity by building tools, workflows, and infrastructure automation. Additionally, you will maintain CI/CD pipelines and enhance observability across the platform to ensure reliable software delivery.
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.
You will architect and operate the infrastructure backbone for gaming platforms, focusing on reliability, scalability, and security. Additionally, you will lead incident response, manage CI/CD pipelines, and implement GitOps-based deployments.
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You will own the platform infrastructure, including Kubernetes, delivery pipelines, and cloud resources across multiple regions. The role involves leading infrastructure migrations, managing production databases, and optimizing cloud costs.
Lead strategic cloud-native migrations and modernize infrastructure with a focus on transitioning enterprise workloads to GitHub Enterprise Cloud. Design and maintain robust internal developer platforms while standardizing tooling and CI/CD pipelines to empower engineering teams.
You will own the end-to-end infrastructure layer for the data platform, including provisioning environments and managing CI/CD pipelines. Additionally, you will implement observability frameworks and ensure data security through robust access controls and cost governance.
You will build and evolve platform infrastructure as code while owning CI/CD pipelines and observability stacks to ensure system reliability. Additionally, you will lead incident response efforts and partner with product engineering teams to eliminate manual toil.
Architect, manage, and scale enterprise Kubernetes infrastructure while driving automation and FinOps principles to ensure efficiency. Collaborate cross-functionally to optimize resource management and mentor engineering teams to maintain technical excellence.
You will architect and optimize the CI/CD ecosystem to support massive containerized infrastructure and drive the adoption of GitOps methodologies. Your role involves collaborating with engineering teams to integrate security, quality gates, and observability into automated deployment pipelines.
You will design, implement, and operate secure, scalable Azure platform capabilities while building infrastructure using Terraform and GitOps processes. Additionally, you will mentor engineers, apply Generative AI to infrastructure tasks, and collaborate with technical teams to drive platform engineering practices.
![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.
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.
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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.
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.
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 engineers, and contribute to technical strategy while leveraging AI-assisted engineering tools.
The engineer will write secure, scalable code for the product platform and own projects from planning to launch. They will also lead efforts to improve system reliability and participate in the team's on-call rotation.
The Senior Data Engineer will maintain and enhance scalable data processes while driving modernization initiatives across the data platform. They will collaborate with cross-functional teams to optimize data pipelines, improve query performance, and ensure system reliability.
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Build and maintain secure, scalable AWS infrastructure to support a production agentic AI platform. Develop Python services and REST APIs while managing cloud infrastructure using infrastructure-as-code practices.
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.
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.
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