DevOps Engineer – Kubernetes & Production Operations (Kubernetes)

Location: Sofia, Bulgaria. Regular working schedule from 13:00 to 22:00. The work model prioritizes in-person collaboration while offering flexibility.

Company

hirify.global is a Fortune 500 global IT services company delivering technical services and projects across industries and geographies.

What you will do

• Maintain and support machine learning applications running on Windows and Linux servers in on-premises production environments.
• Manage, monitor, and troubleshoot Kubernetes clusters and Docker-based workloads hosting machine learning and data science applications.
• Support reliable deployment and operation of machine learning models in production.
• Implement and maintain DataDog monitoring and alerting to protect system health and performance.
• Debug production issues, automate operational tasks, and improve reliability, scalability, maintainability, security, performance, and availability.
• Document system architecture, deployment processes, and troubleshooting guides, and collaborate with engineers and stakeholders.

Requirements

• Proven experience working with Windows and Linux operating systems in production environments.
• Hands-on experience managing on-premises servers, Kubernetes clusters, and Docker containers.
• Strong understanding of Site Reliability Engineering or DevOps practices.
• Familiarity with monitoring and debugging tools such as DataDog.
• Ability to troubleshoot complex issues in distributed systems.
• Experience with CI/CD pipelines for application deployment.
• Familiarity with AWS cloud platforms.
• Strong problem-solving, attention to detail, communication, and collaboration skills.

Nice to have

• Experience supporting production machine learning or data science model deployments.
• Basic understanding of Python for operational support or scripting.
• Familiarity with OT/IT data bridging using Ignition to stream robotics and PLC telemetry into cloud environments or enterprise time-series databases such as InfluxDB, Prometheus, or AWS Timestream.
• Familiarity with machine learning model lifecycle concepts.

Culture & Benefits

• 24 days of paid vacation, comprehensive medical and life insurance, and monthly food vouchers.
• Premium learning platforms, company-sponsored certifications, and continuous development opportunities.
• Employee Recognition and Employee Referral programs.
• Employee discounts, 24/7 wellbeing support for employees and families, and community initiatives.
• International environment focused on collaboration, inclusion, continuous learning, and professional growth.

Hiring process

• Submit a CV in English.
• Only shortlisted candidates will be contacted.