Staff Site Reliability Engineer, Ads

About the role

This is a senior technical leadership role focused on strengthening the reliability of a large-scale advertising ecosystem. You’ll shape reliability strategy across critical systems spanning ad serving, auctions, targeting, reporting, measurement, and billing. The role combines hands-on engineering with architecture, automation, incident leadership, and long-term platform resilience. You’ll partner with engineering leaders and multiple technical teams to influence roadmaps and improve operational excellence. Your work will directly support highly available, low-latency systems where reliability and performance have meaningful business impact. You’ll also mentor engineers and help establish measurable reliability practices across a broad, distributed technology environment.

Accountabilities

• Lead reliability initiatives across critical advertising domains, including ad serving, auctions, targeting, reporting, measurement, attribution, and billing.
• Partner with engineering leadership to establish and execute roadmaps focused on reliability, scalability, operational excellence, and developer productivity.
• Design and build scalable platforms, tooling, automation, and infrastructure capabilities that improve system resilience and engineering efficiency.
• Lead architecture reviews and influence technical decisions for high-traffic, revenue-critical distributed systems.
• Establish and monitor reliability metrics and SLOs around critical advertiser and platform journeys, using data to identify risks and prioritize improvements.
• Participate in on-call rotations, lead complex incident investigations, and coordinate cross-functional responses to major production events.
• Identify systemic reliability risks and implement durable solutions that improve availability, performance, scalability, and operational maturity.
• Drive automation, observability, incident management, performance optimization, and other practices that strengthen production reliability.
• Mentor engineers and provide technical leadership across multiple teams, helping raise engineering standards and reliability expertise.
• Collaborate with Product, Data Science, Infrastructure, and Engineering stakeholders to ensure reliability considerations are embedded into product and infrastructure investments.

Requirements

• 8+ years of experience in Site Reliability Engineering, Infrastructure Engineering, or a related discipline, with experience operating large-scale distributed systems.
• Proven experience evolving and supporting high-traffic, user-facing production environments with demanding availability and performance requirements.
• Deep expertise in distributed systems, scalability engineering, cloud-native architectures, and highly available system design.
• Strong software engineering capabilities, ideally with experience in backend programming languages such as Go.
• Extensive knowledge of observability practices and technologies, including metrics, logging, tracing, alerting, and performance monitoring.
• Demonstrated experience improving reliability through SLOs, automation, incident management, performance optimization, and systematic operational practices.
• Strong troubleshooting and problem-solving abilities across complex, modern distributed technology stacks.
• Excellent cross-functional communication and collaboration skills, with the ability to influence technical direction and align teams around shared reliability goals.
• Experience supporting advertising technology or other large-scale, revenue-critical platforms is highly desirable.
• Familiarity with reliability challenges involving ad serving, real-time auctions, budget pacing, campaign delivery, measurement, attribution, or billing is a strong advantage.
• Experience operating high-QPS, low-latency services where system performance directly affects business outcomes is preferred.
• Experience establishing reliability programs with measurable business and operational results is a plus.
• Hands-on experience with Kubernetes, cloud infrastructure, and large-scale distributed systems is beneficial.
• Familiarity with technologies such as Kafka, ClickHouse, Spark, Flink, or BigQuery is advantageous.
• Experience partnering with Product, Data Science, and advertising engineering teams, or supporting machine learning inference and recommendation systems at scale, is a plus.

Benefits

• Base salary range of $217,000–$303,900 USD, with final compensation determined by factors such as skills, experience, credentials, and role level.
• Eligibility for equity in the form of restricted stock units.
• Comprehensive health benefits, including medical, dental, and vision coverage.
• 401(k) program with employer matching.
• Workspace benefits and support for a home office.
• Personal and professional development funds.
• Family planning support.
• Flexible vacation and global days off.
• 4+ months of paid parental leave.
• Paid volunteer time off.
• Flexible-first remote work environment within the United States.