Senior DevOps Engineer
New
I
IT.HR Recruitment AgencyAI and data infrastructure
Source API remote eligibility restrictions: Albania, Andorra, Austria, Belarus, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czechia, Denmark, Estonia, Faroe Islands, Finland, France, Germany, Gibraltar, Greece, Guernsey, Holy See (Vatican City State), Hungary, Iceland, Ireland, Isle of Man, Italy, Jersey, Kosovo, Latvia, Liechtenstein, Lithuania, Luxembourg, Malta, Moldova, Monaco, Montenegro, Netherlands, North Macedonia, Norway, Poland, Portugal, Romania, San Marino, Serbia, Slovakia, Slovenia, Spain, Svalbard and Jan Mayen, Sweden, Switzerland, Ukraine, United Kingdom, Åland IslandsFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- AWSPythonApache AirflowGCPKubernetesMicrosoft AzureSparkCI/CDTerraformDatabricks
Requirements
- Have 5+ years of professional experience in DevOps, SRE, or Cloud Engineering, focused on mission-critical production systems.
- Have hands-on infrastructure and networking experience with at least one major cloud provider: AWS, Azure, or GCP.
- Bring expert-level knowledge of Kubernetes administration, operation, optimization, scaling, and resource management for production workloads.
- Have practical experience using Terraform for infrastructure provisioning and state management.
- Be proficient in designing and managing CI/CD pipelines, with tools such as Azure DevOps, GitHub Actions, or GitLab CI.
- Have experience with data and AI tooling such as Apache Spark, Apache Airflow, Databricks, or AI/ML infrastructure tooling.
- Be proficient in Python or Bash for automation, testing, and system integration.
- Have experience implementing and working with observability stacks such as Prometheus, Grafana, ELK, or cloud-native monitoring.
Responsibilities
- Design, build, and maintain scalable, secure cloud infrastructure for AI and Big Data solutions.
- Implement automation for ML infrastructure, including model training, real-time inference, and data processing.
- Develop, manage, and optimize Infrastructure as Code using Terraform.
- Create, manage, and improve CI/CD pipelines for code, model, and infrastructure deployments.
- Manage and optimize Kubernetes clusters for containerized data processing and GPU-enabled ML workloads.
- Establish monitoring, logging, and alerting systems for platform health, performance, and cost efficiency.
- Implement security measures, access controls, and compliance frameworks across environments.
- Work with Data Scientists, AI Engineers, and Software Development teams to turn AI requirements into deployable infrastructure.
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