Site Reliability Engineer II, tvScientific

About Pinterest:

Millions of people around the world come to our platform to find creative ideas dream about new possibilities and plan for memories that will last a lifetime. At Pinterest were on a mission to bring everyone the inspiration to create a life they love and that starts with the people behind the product.

Discover a career where you ignite innovation for millions transform passion into growth opportunities celebrate each others unique experiences and embrace theflexibility to do your best work. Creating a career you love Its Possible.

At Pinterest AI isnt just a feature its a powerful partner that augments our creativity and amplifies our impact and were looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities well explore your foundational skills and how you collaborate with AI.

Through our interview process what matters most is that you can always explain your approach showing us not just what you know but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

About tvScientific

tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying optimization measurement and attribution in one efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising digital media and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.

We are seeking a Site Reliability Engineer to help operate scale and continuously improve a cloud-native platform built on AWS Kubernetes/EKS and ArgoCD-driven GitOps workflows. This role will contribute to improving the reliability scalability automation observability and operational maturity of our infrastructure and delivery ecosystem. The ideal candidate is a hands-on engineer with solid production experience and a strong foundation in building and supporting resilient platforms using infrastructure as code automation and modern Kubernetes operational practices.

What youll do:

• Ensuring the reliability availability and performance of production infrastructure and platform services
• Operating and scaling Kubernetes platforms including governance and support for multi-tenant workloads
• Managing GitOps-based deployment workflows using ArgoCD and Helm
• Supporting infrastructure provisioning and change management through Terraform/Terragrunt
• Building and supporting CI/CD automation and deployment workflows using GitHub Actions
• Participating in incident response root cause analysis and post-incident improvement initiatives
• Reducing operational toil through scripting tooling and process automation
• Advancing observability practices across logs metrics traces dashboards and alerting
• Supporting secure secrets integration IAM-aware operations and platform guardrails
• Partnering closely with application security and platform teams to improve reliability and delivery outcomes

What were looking for:

• 4 years of experience in Site Reliability Engineering DevOps Platform Engineering or Cloud Infrastructure
• Strong hands-on experience operating AWS in production environments
• Good expertise in Kubernetes including cluster operations troubleshooting workload reliability and platform administration
• Experience with Kubernetes multi-tenancy including namespaces RBAC quotas policies and tenant isolation patterns
• Experience implementing and operating ArgoCD within a GitOps delivery model
• Strong hands-on experience with Helm
• Experience with Terraform/Terragrunt for infrastructure provisioning and environment management
• Solid scripting and automation skills using Bash and/or Python
• Experience building maintaining or supporting CI/CD pipelines ideally using GitHub Actions
• Strong troubleshooting skills across Linux containers IAM networking and distributed systems
• Experience with monitoring alerting and observability in production environments
• Demonstrated ownership mindset with experience handling incidents and resolving production issues
• Strong collaboration and communication skills with the ability to work effectively across engineering security and platform teams
• Bachelors degree in computer science engineering a related field or equivalent experience
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
• Strong track record of critical evaluation and verification of AI-assisted work (e.g. testing source-checking data validation peer review)
• High integrity and ownership: you protect sensitive data avoid over-reliance on AI and remain accountable for final decisions and deliverables

In-Office Requirement Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

Relocation Statement:

• This position is not eligible for relocation assistance. Visit ourPinFlexpage to learn more about our working model.

#LI-SM4

#LI-REMOTE