Job responsibilities

• Design, implement, and optimize SRE best practices for AI/ML infrastructure, focusing on reliability, scalability, security, and operational efficiency.
• Develop and maintain automated monitoring, alerting, and incident response systems.
• Manage day-to-day support issues, conduct root cause analysis, and drive continuous improvement to reduce repeat errors and enhance system stability.
• Demonstrates and champions site reliability culture and practices and exerts technical influence throughout your team
• Leads initiatives to improve the reliability and stability of your team’s applications and platforms using data-driven analytics to improve service levels
• Collaborates with team members to identify comprehensive service level indicators and stakeholders to establish reasonable service level objectives and error budgets with customers
• Demonstrates a high level of technical expertise within one or more technical domains and proactively identifies and solves technology-related bottlenecks in your areas of expertise
• Acts as the main point of contact during major incidents for your application and demonstrates the skills to identify and solve issues quickly to avoid financial losses
• Documents and shares knowledge within your organization via internal forums and communities of practice

Required qualifications, capabilities, and skills

• 5+ years in site reliability or infrastructure engineering roles.
• Deep expertise in AWS cloud services, infrastructure automation (Terraform, CloudFormation), and monitoring tools (Prometheus, Grafana, CloudWatch).
• Strong problem-solving, communication, and collaboration skills.
• Experience with CI/CD pipelines, operational stability, and risk management.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field (or equivalent experience).
• Deep proficiency in reliability, scalability, performance, security, enterprise system architecture, toil reduction, and other site reliability best practices with the ability to implement these practices within an application or platform
• Fluency in at least one programming language such as (e.g., Python, Java etc.)
• Deep knowledge of software applications and technical processes with emerging depth in one or more technical disciplines
• Proficiency and experience in observability such as white and black box monitoring, SLO alerting, and telemetry collection using tools such as Grafana, Dynatrace, Prometheus, Datadog, Splunk, etc.
• Proficiency in continuous integration and continuous delivery tools (e.g., Jenkins, GitLab, Terraform, etc.)
• Experience with container and container orchestration (e.g., ECS, Kubernetes, Docker, etc.)
• Experience with troubleshooting common networking technologies and issues
• Drive to self-educate and evaluate new technology
• Advanced English skills

Please submit your resume in English