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