As a Site Reliability Engineer at Flip, your primary responsibilities will include ensuring the availability and performance of our infrastructure, promoting CI/CD practices, and optimizing our cloud systems. You'll play a key role in scaling our cloud infrastructure, managing our Kubernetes cluster, and enhancing our observability tools. Engaging with technologies like Pulumi and creating infrastructure as code will also be part of your day-to-day tasks, all while collaborating with a motivated team dedicated to reforming the way frontline employees experience their work.

To be a strong candidate for the Site Reliability Engineer role at Flip, you should have experience in managing cloud infrastructures such as AWS, Azure, or GCP, along with deep knowledge of Kubernetes and container solutions. Familiarity with observability frameworks and software development skills in languages like Go, Python, or Kotlin are also essential. If you have experience with automation tools and infrastructure as code using Pulumi or similar technologies, it will be a significant advantage.

The work culture at Flip for a Site Reliability Engineer emphasizes collaboration, fun, and flexibility. You will find a relaxed atmosphere with highly motivated colleagues who are committed to making a difference. We prioritize work-life balance and ensure that our employees happy and engaged in their roles. Regular team events and culture days foster camaraderie while inspiring personal and professional growth, making Flip not just a workplace but a community.

Yes, the Site Reliability Engineer position at Flip offers the flexibility of a fully remote setup, particularly for candidates located within Europe. You have the option to work from home, choose a hybrid style in our modern offices in Stuttgart or Berlin, or even work abroad within the European Union. This autonomy helps our team members maintain a balance between their professional and personal lives.

As a Site Reliability Engineer at Flip, you will engage with a variety of cutting-edge tools and technologies. Your primary focus will be on cloud platforms like AWS, Azure, or GCP, as well as container orchestration solutions like Kubernetes. Additionally, you will work with observability tools such as Grafana, Prometheus, and Loki to create and maintain system visibility. Familiarity with infrastructure as code using Pulumi, automation tools like Ansible or Chef, and modern programming languages like Go will also be crucial to your success in this role.

To ensure system reliability in my previous projects, I focused on several key areas: implementing rigorous monitoring and alerting systems, conducting regular chaos engineering exercises, and emphasizing automation for deployment processes. By continuously measuring service-level objectives and adjusting our approach based on observed performance, I was able to effectively increase system resilience.

In my experience with Kubernetes, I've managed container orchestration, optimized resource allocation, and ensured high availability of services. I've used Helm for package management and implemented monitoring solutions for clusters. My role involved troubleshooting issues and performing upgrades, always with minimal downtime to maintain reliability and performance.

I utilize Jenkins and GitLab CI/CD for managing CI/CD pipelines, which automate the building, testing, and deployment processes. Integrating unit tests and performance tests in the pipeline ensures that only well-tested code gets promoted to production. Additionally, I advocate for blue-green deployments and canary releases to mitigate risks during production updates.

When a service goes down, my immediate priority is to assess the impact and initiate an incident response plan. This includes identifying the root cause through logs and metrics, communicating with stakeholders about the issue, and working collaboratively with the team to implement a fix as quickly as possible. Post-incident, I conduct a blameless retrospective to understand what went wrong and refine our processes to prevent recurrence.

I have extensive experience with infrastructure as code, primarily using Pulumi and Terraform to manage and provision cloud resources. This practice allows for more consistent environments, version control, and easier replication of infrastructure. I focus on modularizing code, enabling easy updates, and promoting best practices across teams to enhance collaboration and efficiency.

I advocate for creating an observability culture within teams by integrating logging, metrics, and tracing into our applications. Using tools like Prometheus for metrics collection and Grafana for visualization enables us to monitor system performance effectively and quickly diagnose issues. Setting up alerts based on error budgets or SLO targets helps maintain a resilient system.

I am proficient in several programming languages, including Go and Python. I’ve used Go to develop microservices that are both scalable and efficient, while Python has been instrumental in scripting automation tasks and leveraging APIs for monitoring tools. This combination allows me to build robust applications that align with SRE principles.

When managing multiple incidents, I prioritize tasks based on severity and potential impact on users. Creating a triage system that categorizes issues by urgency helps me address the most critical ones first. Furthermore, clear communication with stakeholders ensures everyone is informed, which aids in managing expectations throughout the incident lifecycle.

Service-level objectives (SLOs) define the target level of reliability for a service, typically expressed as a percentage of uptime or success rate. They are crucial for guiding developers, and as an SRE, I ensure regular assessments of SLOs to align with business objectives, adjusting as necessary based on risks and feedback from incident postmortems.

A challenging problem I encountered was managing traffic spikes during a major event. We implemented auto-scaling in conjunction with a load-balancer to handle sudden increases in user activity. By closely monitoring system metrics, we ensured that resources were allocated dynamically, which ultimately maintained service availability and user satisfaction despite the high load.