DevOps Engineer

DevOps engineers build, test and maintain the infrastructure and tools to allow for the speedy development and release of software. DevOps practices aim to simplify the development process of software and help us improve our operating systems. This role has a strong background in software engineering and will employ DevOps tools and practices to improve the development team’s production and guide our hardworking team through the process of designing and writing a dependable codebase. This position also allows to innovate our engineering systems and practices. The role is expected to work in an AI-native way, using AI coding assistants and agents (such as Claude, GitHub Copilot, Cursor, and Antigravity) to accelerate automation, scripting, and troubleshooting.

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• Establish and optimize DevOps methodologies and standards.

• Ensure effective collaboration and communication between development

• and operations teams.

• Integrate security practices into all DevOps processes.

• Development, deployment, and maintenance of software products and infrastructure.

• Achieve and maintain a high level of operational efficiency by automating routine tasks, reducing deployment times, and minimizing downtime, particularly within AWS environments.

• Leverage AI coding assistants (GitHub Copilot, Cursor, Antigravity, Claude) to speed up scripting, automation, and routine engineering tasks while maintaining quality and security standards.

• Design, implement, and maintain robust CI/CD pipelines to automate deployment processes across multiple environments.

• Apply cloud (AWS) computing skills to deploy upgrades and fixes.

• Design, develop and implement software integrations.

• Develop and manage infrastructure using tools like Terraform, Ansible, or CloudFormation to ensure scalability, reliability, and security.

• Troubleshoot production issues and coordinate with the development team to streamline code deployment.

• Implement and maintain monitoring solutions to ensure system health, performance, reliability, uptime, and security.

• Lead incident response efforts to quickly resolve production issues.

• Conduct systems tests for security, performance, and availability.

• Use AI assistants such as Claude to accelerate log analysis, root-cause investigation, and incident post-mortems.

• Implement security best practices in the CI/CD pipeline and throughout the infrastructure to protect sensitive data and ensure compliance with industry standards.

• Apply AI-assisted code review to help identify vulnerabilities and harden configurations earlier in the development lifecycle.

• Identify and implement improvements in processes, tools, and automation to enhance efficiency and reduce manual intervention.

• Develop and maintain design and troubleshooting documentation.

• Implement automation tools and framework.

• Adopt and continuously improve AI-assisted workflows, sharing effective prompts and practices with the team.

• Work closely with developers, QA, and other stakeholders to streamline the release process, improve code quality, and ensure seamless integration.

• Collaborate with team members to improve the company’s engineering tools, systems and procedures, and data security.

• Strong experience in DevOps tools and technologies particularly in environments that prioritize continuous delivery and automation, with a focus on AWS services and configuration (EC2, RDS, CloudFront, Athena, Lambda, MediaConvert, etc.).

• Work with a non-managed Kubernetes cluster.

• Proficiency in programming languages such as Python, PHP, and others relevant to the tech stack.

• Experience with Databases such as MySql, PostgreSQL, ClickHouse

• Experience with DevOps tools and platforms such as IaC: Terraform, Ansible, Helm. Git, Docker, Kubernetes, Bitbucket Pipelines and AWS/Oracle (CloudFront, ECS, EKS, EC2, S3, IAM, EFS, WAF, etc). ELK-stack, Prometheus, Grafana.

• Hands-on experience using AI coding assistants and agents to accelerate engineering work — including GitHub Copilot, Cursor, and Antigravity.

• Experience with Claude is a significant plus; the ability to use it effectively for code generation, log and incident analysis, documentation, and troubleshooting is highly valued.

• Sound judgment in applying AI output responsibly — reviewing, validating, and securing AI-generated code and configurations before use.

• Strong analytical and problem-solving skills with the ability to troubleshoot complex issues in a dynamic environment.

• Excellent decision-making skills.

• Excellent communication skills with the ability to work collaboratively across teams.

• Advanced English proficiency, both written and spoken, is mandatory for effective communication with partners and clients.