115 Platform Engineer jobs in Germany available for remote work from home. Apply for positions such as Senior Backend Engineer - Energy Management Platform (all genders), Senior Platform / Backend Engineer (m/w/d) – IAM & Core Services, (Senior) Platform / DevOps Engineer – Kubernetes & Infrastruktur (m/w/d) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will own features end-to-end, from analysis and implementation to production, while ensuring system reliability and scalability. Additionally, you will drive architectural decisions, mentor teammates, and maintain high-quality documentation to support team growth.
You will manage the identity and access management infrastructure, develop self-service portals, and architect event-streaming solutions using Apache Kafka. Additionally, you will ensure secure software delivery through code signing and implement monitoring concepts to maintain platform reliability.
Build and automate stable infrastructure landscapes, focusing on the operation and security of multiple Kubernetes clusters and Linux systems. Translate compliance standards like C5 and ISO 27001 into technical controls and implement security-by-design practices.
Lead the migration of mission-critical data pipelines from legacy Hadoop and Spark environments to a cloud-native Databricks architecture. Design and optimize scalable data workflows using Airflow while leveraging AI coding assistants to accelerate development.
The role involves operating and developing IT infrastructure, focusing on Linux systems and Kubernetes environments. Responsibilities include managing network components like nginx and HAProxy, as well as optimizing various database and messaging technologies.
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Build and manage the platform for the AI Solver, including training data pipelines and the model lifecycle from experiment to production. Operate and scale the AWS service that serves AI models to customers while ensuring reliability and monitoring.
Lead the end-to-end evolution of a GKE-based identity platform, focusing on cluster design, multi-region resilience, and technical roadmapping. Establish modern CI/CD pipelines, GitOps workflows, and ensure regulatory compliance within a Tier-1 banking environment.
You will be responsible for the technical architecture of deployment, setup, and automation logic for the BI platform. Additionally, you will develop and maintain scalable Power BI workspace structures and automate release processes using Power Automate and REST APIs.
You will be responsible for the technical structure of deployment, setup, and automation logic while strategically developing the internal platform for customer onboarding. Additionally, you will architect Power BI workspace structures and implement robust logging, monitoring, and governance mechanisms.
The role focuses on building robust infrastructure rather than just processing tickets, aiming to enable teams to ship faster through platform design and automation. Responsibilities include designing and automating developer platforms, integrating modern tools into DevOps pipelines, shaping the Google Cloud Kubernetes infrastructure, and proactively hardening systems.
You will own the reliability, performance, and observability of the entire inference stack. This includes designing telemetry pipelines, tuning Kubernetes autoscalers, and creating automation for incident management.
You will design, build, and maintain critical backend services for card issuance and transaction processing using Java and Spring Boot. Additionally, you will manage platform reliability through observability, incident response, and proactive capacity planning.
You will design, build, and maintain scalable cloud infrastructure while collaborating with software engineers to meet their infrastructure needs. Additionally, you will automate routine processes and enhance CI/CD pipelines to improve operational efficiency and system reliability.
The Senior Platform Engineer will own developer experience and application frameworks while bridging the gap between DevOps and data engineering. They will also build automation for data quality checks and mentor the engineering team through code and design reviews.
Lead a platform engineering team by setting technical direction, conducting design and code reviews, and managing day-to-day delivery. Collaborate with product, bring-up, and security teams to translate requirements into scalable, production-grade platform capabilities.
Drive the product vision and roadmap for internal platform engineering tools to improve developer experience and software delivery. Partner with engineering and security teams to implement cloud infrastructure, CI/CD, and AI-driven agentic workflows.
Drive the product vision and roadmap for internal platform engineering tools to improve developer experience and software delivery. Align technical capabilities with business impact and enable AI-driven engineering workflows.
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The AI Platform Engineer/Lead will design and build internal AI frameworks and enable teams to integrate AI features seamlessly. They will also own AI tooling from experimentation to production and define best practices for AI usage.
You will lead the Platform Core team, owning the roadmap for infrastructure, IAM, and networking foundations while managing the team's growth. You will also oversee the compute migration from ECS/Fargate to Kubernetes and ensure internal engineering teams have a reliable, scalable platform.
Lead and mentor a team of engineers responsible for the company's data foundation and ML operations lifecycle. Oversee the reliability and scalability of the internal data warehouse while collaborating with cross-functional teams to drive product outcomes.
Lead a new team of AI Software and Platform Engineers to transition AI concepts into scalable, production-grade backend systems. Drive the end-to-end implementation of AI use cases and shape the internal AI platform for model access, governance, and cost management.
Lead a new team of AI Software and Platform Engineers to bring AI use cases into production at scale. You will provide technical direction for LLM services and backend systems while collaborating with stakeholders to deliver high-value AI capabilities.
Lead a new team of AI Software and Platform Engineers to transition AI concepts into scalable, production-grade backend systems. Drive the end-to-end implementation of AI use cases and shape the internal AI platform for secure and cost-effective model access.
You will lead and develop a multidisciplinary data engineering team while setting the technical direction for the platform that processes billions of payment events. You will also collaborate with cross-functional teams to ensure data products are reliable, scalable, and compliant with industry standards.
You will architect and automate Power BI deployment processes and manage the platform's technical structure. Additionally, you will collaborate with product and customer success teams to translate requirements into stable, scalable data architectures.
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