building and maintaining the reliability, scalability, and performance e of our digital media measurement platforms
Leverage AI-assisted development tools to accelerate automation development and problem resolution
Build custom integrations and MCP servers for monitoring platforms to enable programmatic access and AI-driven analysis
Implement observability best practices , including metrics collection, dashboarding, and alerting strategies that support proactive reliability improvements
Monitor and maintain high availability infrastructure and services across GCP, AWS, and on-premises environments
Respond to incidents and drive them to resolution, managing Sev1/Sev2 situations
Reduce MTTR for critical incidents through automation, improved observability, and proactive monitoring
Build and deploy automations to eliminate operational toil and improve efficiency across deployment workflows, validation scripts, and self-service capabilities
Implement Infrastructure-as-Code using Terraform, Helm charts Python and scrips, and configuration management tools to ensure repeatable, version-controlled infrastructure deployments
Develop production automations for routine operational tasks, reducing manual intervention and accelerating task completion
Create and maintain documentation , runbooks, and SOPs in Confluence to ensure consistent incident response across the team
Participate in on-call rotations and post-incident reviews to minimize downtime and prevent recurrence
Lead technical projects from planning through deployment, ensuring proper stakeholder communication and team enablement
Required Experience & Skills
4+ years in Site Reliability Engineering, DevOps, or related operational roles with proven experience in Linux/Unix systems administration
proficiency in scripting and programming languages such as Python, Bash, or Go for automation and tool development
Strong experience with cloud platforms, and container orchestration tools like Kubernetes
Expertise in monitoring and observability tools such as Prometheus, Grafana, Splunk, Nagios,
Hands-on experience with Infrastructure-as-Code tools like Terraform, Ansible, or Helm
Proven ability to develop and track SLIs, SLOs, and SLAs to drive reliability improvements
Technical Knowledge
Deep understanding of networking, DNS, load balancing, and CDN technologies
Familiarity with databases (SQL, NoSQL, Vertica, MongoDB, Snowflake) and data pipeline technologies
Knowledge of CI/CD pipelines, GitLab, and deployment automation
Experience with workflow automation platforms is a strong plus
Soft Skills & Mindset
Exceptional communication skills with the ability to collaborate across teams and explain technical concepts clearly
Proactive problem-solving approach with a focus on automation and continuous improvement
Ownership mentality — you take full responsibility for complex challenges and reliably deliver outcomes
Trailblazing spirit — innovative use of AI, automation, and new technologies to solve problems and drive improvements
Passion for mentorship and knowledge sharing, elevating the capabilities of the entire team
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Engineering, or related field
Industry certifications such as AWS Certified DevOps Engineer , Google Professional Cloud DevOps Engineer , Certified Kubernetes Administrator (CKA) , or Terraform/Grafana certifications
Experience with AI-assisted development using tools like ChatGPT, Cursor, Glean, or Copilot
Familiarity with security best practices in cloud and containerized environments