Вакансия DevOps Engineer

Skills

• AWS
• Azure
• GCP
• Kubernetes
• Cloud Storage
• Python
• Bash
• Shell
• Jenkins
• GitLab CI/CD
• CircleCI
• Docker
• Helm
• Terraform
• Ansible
• AWS CloudFormation
• DNS
• SSL
• TLS
• Grafana
• ELK
• Datadog

Описание вакансии

We are looking for a skilled DevOps Engineer to design, implement, and maintain scalable, secure, and robust infrastructure to support AI-driven solutions. This role involves working closely with cross-functional teams to optimize performance, enhance deployment processes, and ensure the stability of complex systems in a dynamic environment.

Requirements

• Minimum 4 years in DevOps, SRE, or similar roles with a strong focus on cloud environments and automation.
• Hands-on experience with AWS, Azure, and GCP, including Kubernetes, Cloud Storage, Load Balancers, and AI/ML-specific services.
• Proficiency in scripting languages like Python, Bash, or Shell, as well as tools like Jenkins, GitLab CI/CD, and CircleCI.
• In-depth knowledge of Docker and Kubernetes (preferably with Helm) for application deployment and orchestration.
• Practical experience with Terraform, Ansible, and CloudFormation for infrastructure management.
• Strong understanding of networking concepts, including DNS, SSL/TLS, and load balancing in cloud environments.
• Experience configuring observability solutions like Grafana, ELK, or Datadog.
• Proven track record in implementing security measures for cloud deployments, CI/CD pipelines, and data protection.
• Strong interpersonal and communication skills to effectively work with cross-functional teams.

Preferred qualitifcations

• AWS Certified DevOps Engineer, Azure DevOps Engineer Expert, or Google Professional Cloud DevOps Engineer.
• Experience managing and optimizing multi-cluster Kubernetes environments.
• Familiarity with AI/ML workflows and data pipelines.
• Expertise in designing and managing disaster recovery strategies for mission-critical systems.

Responsibilities

• Build, deploy, and manage cloud-based infrastructure on platforms such as AWS, Azure, and GCP, tailored for large-scale AI applications.
• Develop and optimize CI/CD pipelines to enable smooth and automated software delivery for AI workloads.
• Utilize tools like Terraform, CloudFormation, and Ansible to ensure consistent, scalable, and repeatable infrastructure deployments.
• Implement containerized environments using Docker and Kubernetes (including Helm) to ensure efficient resource utilization and high availability.
• Set up and manage monitoring, logging, and alerting solutions (e.g., Prometheus, Grafana, ELK stack, Datadog) to maintain system reliability and performance.
• Implement and enforce best practices in security and compliance across all infrastructure and DevOps processes.
• Partner with AI, data science, and development teams to align infrastructure with project needs and AI workload demands.
• Research and adopt emerging DevOps tools and methodologies to enhance operational performance.