DevOps Engineer

Company description:

Who are we?Volvo Cars is a company on a mission; to bring traditional car manufacturing into a connected, sustainable and smart future.Since 1927, we have been a brand known for our commitment to safety, creating innovative cars that make life less complicated for our consumers. In 2010, we decided to transform our business, resulting in a totally new generation of cars and technologies, as well as steady growth and record sales. Today, we’re expanding our global footprint in Europe, China and the US, and we’re on the lookout for new talent. We are constantly pushing our own skills and abilities to drive change in the automobile industry like never before. We are looking for innovative, committed people to join us in this endeavour and create safe, sustainable and connected cars. We believe in the power of people and will challenge and support you to reach your full potential. Join us and be part of Volvo Cars’ journey into the future.

Job description: Let's introduce ourselves

We are seeking a new talented DevOps Software Engineer to help shape the future of observability in modern infrastructure.Are you passionate about building tools that empower teams to operate at scale? Join our collaborative engineering team to design, develop, and support observability platforms that give deep insight into complex, cloud-native environments.In this role, you’ll work closely with engineers and architects to integrate and enhance monitoring, logging, and tracing systems across Kubernetes clusters—using GitOps principles to keep everything versioned, automated, and reliable.We're looking for someone who thrives in fast-paced environments, communicates clearly, and enjoys solving real-world operational challenges with clean, scalable code.

What you'll do

 

• Experience with Kubernetes and cloud-native ecosystems
• Familiarity with observability stacks (e.g., Prometheus, Grafana, Loki, Splunk, OpenTelemetry)
• GitOps mindset and tools (e.g., ArgoCD, Flux)
• A collaborative, team-first attitude and a sharp eye for automation opportunities

Let’s build systems that don’t just run – tell us how they’re running.

Profile description: What you'll bring

We believe you bring 2–10 years of experience working with cloud infrastructure, with a strong focus on implementing observability solutions—including log management, metrics, and tracing. You have a solid understanding of technical architecture and hands-on experience in the design, development, and delivery of projects across various domains.You likely hold a BSc or higher degree in Computer Science, Engineering, or a related technical field—or have equivalent practical experience.Key Responsibilities: 

• Design and Implement Observability Solutions: Build and maintain observability tools (monitoring, logging, metrics, tracing) to ensure the health and performance of microservices running on AWS.
• Monitoring & Logging: Set up and optimize monitoring using tools like Prometheus, Grafana, CloudWatch, OTEL and Splunk stacks for real-time insights into the AWS infrastructure.
• Distributed Tracing: Implement distributed tracing solutions (e.g., OpenTelemetry, Tempo) to trace and debug service interactions across multiple microservices.
• Proactive Alerting: Establish alerting mechanisms to detect performance anomalies and potential failures in real-time.
• Dashboards & Reporting: Create dashboards and reports to monitor and secure service-level objectives (SLOs), key performance indicators (KPIs), and overall system health.
• Incident Management: Investigate and troubleshoot issues, identifying root causes, and providing insights to reduce mean time to detection (MTTD) and mean time to resolution (MTTR).
• Collaboration with Teams: Collaborate with DevOps and development teams to ensure observability best practices are embedded into CI/CD pipelines and infrastructure as code (IaC) practices.
• Automation & Optimization: Take part and lead any initiatives that will help us operate in more efficient manner whereby embracing AI will be a pre-requisite.

Tool chain used:

• Frameworks: Docker, Kubernetes
• Infrastructure: AWS
• Development & GitOps tools: Gitlab, ArgoCD, Harbor, Sonarqube, Dependency Tracker, GIT
• Observability support tools: OTEL, Splunk, Loki, Tempo, Prometheus, Pagerduty, Apica, Grafana, Slack, Confluence, Jira, AI Agent (HolmesGPT + Azure foundry)
• SW Languages: Python, Java, JavaScript, Typescript, Terraform, Ansible