DevOps / MLOps Specialist

Role overview Build and operate the infrastructure behind AI agent and automation services, with an emphasis on reliable, secure deployments that can scale. The role spans container environments, cloud resources, delivery pipelines, monitoring, and the operational controls needed to support production workloads.

Responsibilities - Set up and secure Docker environments for agents, workflow tools, and supporting services. - Build and improve CI/CD pipelines for automation logic, language model workflows, and infrastructure changes. - Manage cloud infrastructure with attention to service performance and cost. - Automate provisioning and orchestration using tools such as Ansible or Terraform. - Deploy containerized AI and machine learning models with monitoring, scaling, and rollback support. - Configure network protections and operational monitoring; maintain access controls, TLS/SSL, and backups.

Requirements - Three to five or more years of experience in DevOps, MLOps, or infrastructure engineering for SaaS or automation platforms. - Proven experience with Docker, Linux systems, and cloud or VPS environments. - Ability to create and operate CI/CD pipelines and infrastructure automation. - Experience monitoring deployed services and addressing reliability and security needs.

Nice to have - Exposure to MLOps practices, including model versioning, deployment pipelines, and inference optimization. - Experience supporting globally distributed or multilingual teams.

Benefits and work setup - Full-time remote position with flexibility in time and location, subject to working from an eligible country. - Annual training allowance of 12 days, including six days chosen by the employee. - Team activities and a salary package are mentioned, but no specific compensation details are provided.