Top Software Engineer Jobs

As a Test Automation Engineer, you will develop and enhance automated testing frameworks for payment terminal firmware, collaborating with other developers to improve testing processes and tools. You will work with a diverse tech stack, focusing on API development and user interfaces for scheduling and analyzing tests, contributing to the reliability of payment processing.

The Senior Linux Infrastructure Engineer will design, maintain, and automate critical infrastructure services including load balancers and DNS. Responsibilities include optimizing infrastructure, collaborating with product teams for scalable solutions, driving innovations, and participating in architectural decisions to enhance reliability and performance.

As a Data Platform Engineer at Adyen, you will develop and maintain scalable big data platforms, collaborating with diverse stakeholders. Responsibilities include building new tools, improving existing systems, enhancing data quality, and working with various distributed systems and DevOps pipelines.

The Engineering Manager for the Accounting Platform at Adyen will lead a team of 4 to 8 engineers, focus on the growth and maintenance of the platform, and ensure technical excellence in design and implementation. Responsibilities include managing projects, mentoring the team, fostering a collaborative environment, and aligning goals with product management.

As a Software Engineer on the Observability team, you will design APIs, improve software reliability, manage telemetry data, troubleshoot production issues, and collaborate with other teams to enhance the overall observability platform.

As a Java Software Engineer, you'll manage the full development cycle, design software, and ensure successful deployment. You will work with a massive PostgreSQL database, focus on building a high-performance platform, and collaborate across teams to enhance system robustness and scalability.

The Machine Learning Engineer in the MLOps team will develop, deploy, and operate MLOps tooling and services, handle model training and tracking, ensure stable model deployment, and oversee infrastructure scalability while collaborating with data science teams.