Staff Site Reliability Engineer

Visa

Stockholm, SEonsitePosted Jul 21, 2026
Posting intelligenceActively listedReposted 27×, possible evergreen/ghost posting

Skills

prometheusterraformansiblegrafanadatadogspringpythonazureflinkjavagooglecloudawsgoml

About the role

About Us

Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid.

At Visa, you'll have the opportunity to create impact at scale - tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world.

Join Visa and do work that matters – to you, to your community, and to the world. Progress starts with you.

Job Description

The Staff Site Reliability Engineer is responsible for architecting, implementing, and maintaining solutions that ensure Visa’s application services operate with high availability and reliability. This role focuses on automating operational tasks, monitoring system performance, and supporting incident response to optimize the reliability and efficiency of global payment systems. The engineer collaborates with cross-functional teams to drive innovation, influence architectural decisions, and build systems that process billions of transactions. The position requires expertise in modern application technologies, cloud platforms, containerization, and observability tools, as well as a commitment to continuous improvement and knowledge sharing.

All roles require digital fluency, including the ability to work with emerging technologies such as Generative AI tools (e.g. ChatGPT, Microsoft Copilot) to support everyday work.

Key Responsibilities:

Architect and implement solutions to maintain “Always On” availability for Visa’s application services.

Automate monitoring, deployment, and incident response processes to improve efficiency and reliability.

Lead investigations and troubleshooting activities to resolve complex technical issues and prevent future incidents.

Collaborate with global engineering teams to build, support, and deploy application services.

Drive the evolution from traditional applications to cloud-native solutions, influencing architectural decisions.

Build and maintain documentation repositories to facilitate knowledge transfer among peers.

Participate in on-call rotations to support business operations, including off-hours.

Support and optimize ML model deployment pipelines and monitoring systems.

Assist in automating routine tasks and processes to reduce human errors.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Qualifications

Basic Qualifications:

Relevant work experience with a Bachelor’s Degree, Advanced degree (e.g. Masters, MBA, JD, MD) or a PhD, or relevant work experience.

Preferred Qualifications:

Experience in containerized micro-services architecture and stacks.

Experience in designing and deploying high-performance applications using modern technologies (e.g., Tomcat, Apache, Spring Boot, SQS, JBoss, IBM MQ, IBM DataPower, Hazelcast, Flink, Connect Direct, SSL).

Experience in leveraging cloud platforms such as AWS, Azure, and GCP for scalable and resilient infrastructure solutions.

Experience in using infrastructure-as-code tools such as Terraform and Ansible to automate deployment and management.

Experience in monitoring and logging systems including Prometheus, Grafana, Datadog, and the ELK stack.

Experience in automating complex tasks and processes using programming languages such as Python, Go, and Java.

Experience in supporting and optimizing ML model deployment pipelines and monitoring systems.

Experience in building and maintaining documentation repositories for infrastructure and operational procedures.

Experience working with Agile teams.

Experience in fast-paced 24x7 environments.

Experience in distributed systems design and maintenance.

Experience in cloud and system architecture across hybrid platforms (AWS, GCP, Azure).

Experience in observability and performance optimization techniques.

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