Lead Site Reliability Engineer

Job responsibilities

• 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

• Formal training or certification on site reliability Engineering concepts and 5+ years applied experience
• Expertise in application development and support with multiple technologies and design techniques.
• Experience in developing AI/ML solutions using public cloud architecture, specifically Azure and AWS and experience in Python for AI/ML modeling.
• Experience in automation and continuous delivery methods.
• Familiarity with agile methodologies, including CI/CD, application resiliency, and security.
• Experience in implementing GenAI services using Azure OpenAI models and AWS Bedrock service.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
• 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

• Ability to identify and solve problems related to complex data structures and algorithms