DevOps Engineer (Medellín)

As a DevOps Engineer at Coactive, your primary responsibilities include designing and maintaining cloud infrastructure, optimizing CI/CD processes, managing real-time data workflows, implementing monitoring solutions, and ensuring robust cloud security practices. You'll collaborate with our ML and data engineering teams to seamlessly integrate support systems that enhance our AI capabilities.

To apply for the DevOps Engineer position at Coactive, candidates should have over 5 years of experience in cloud infrastructure, particularly AWS. Familiarity with GCP and Azure is also advantageous. Additionally, candidates should have expertise in Kubernetes, data platforms like Kafka and Spark, and strong Python programming skills for automation.

Yes, the DevOps Engineer position at Coactive is remote-friendly, allowing you to work from Medellín, Colombia, while being part of a dynamic and supportive team. This flexibility encourages a healthy work-life balance while you contribute to innovative projects in AI and data management.

A DevOps Engineer at Coactive should be well-versed in cloud platforms like AWS, GCP, and Azure. Familiarity with container orchestration tools such as Kubernetes, data processing technologies like Kafka and Spark, and monitoring tools such as Datadog are also essential. Strong networking skills and experience with databases like MongoDB and Postgres are important as well.

At Coactive, the team culture is collaborative and innovative. We believe in fostering a supportive environment where team members can thrive and develop their skills. As a DevOps Engineer, you'll work closely with experts from various backgrounds, empowering each other to solve complex challenges in a fast-paced startup atmosphere.

When answering this question, focus on specific projects where you designed or managed cloud environments, particularly using AWS, GCP, or Azure. Mention the scale of the infrastructure, the technologies employed, and any improvements in performance or cost-efficiency you achieved.

Discuss your experience with automation in CI/CD processes, including the tools you’ve used, such as Jenkins or Azure DevOps. Provide examples of how you optimized these pipelines for faster deployment with minimized errors, highlighting any key metrics you tracked for performance.

Outline the monitoring tools you've employed, like Datadog or Prometheus, and relevant metrics you prioritize, such as uptime and latency. Describe a specific incident where your monitoring helped identify and resolve an issue quickly.

Share your proficiency with Kubernetes, including any specific use cases where you've utilized it to scale applications or manage workload efficiently. Discuss any challenges faced and how you overcame them.

Talk about the security measures you prioritize, such as identity management, encryption at rest and in transit, and compliance with industry standards. Mention a time when you identified a vulnerability and successfully implemented a solution.

Explain your systematic approach to diagnosing performance issues, mentioning tools and logs you analyze to identify bottlenecks, and how you prioritize addressing them to minimize impact on users.

Share specific examples of previous projects where you worked with data engineers or ML teams. Discuss how you ensured a smooth integration of infrastructure tools with machine learning workflows.

Discuss fundamental networking concepts such as IP addressing, DNS, load balancing, and firewalls. Provide instances where your understanding of these concepts helped improve system architecture in previous roles.

Describe your experience with Infrastructure as Code (IaC) using Terraform. Share how you've utilized it to provision and manage cloud resources, and mention any specific deployment pipelines you've created.

Reflect on your adaptability and problem-solving skills. Share examples of how you've managed changing priorities, communicated effectively, or optimized solutions under tight deadlines.