Staff Site Reliability Engineer (Ads)

TL;DR

Staff Site Reliability Engineer (Ads): Leading reliability initiatives for Reddit's advertising platform with an accent on scalability, operational excellence, and developer productivity. Focus on designing high-availability infrastructure, driving architecture reviews for revenue-critical systems, and mentoring engineering teams across the Ads organization.

Location: Must be based in the UK, the Netherlands, or Ireland

Company

Reddit is a community-driven platform home to over 100,000 active communities and millions of daily visitors, facilitating open and authentic conversations globally.

What you will do

• Lead reliability initiatives across ad serving, auctions, targeting, reporting, and billing domains.
• Partner with engineering leadership to drive architecture reviews and influence technical decisions for revenue-generating systems.
• Design and build platforms, tooling, and automation to improve system resilience and developer efficiency.
• Coordinate cross-functional response efforts during major production events and lead complex incident investigations.
• Establish and monitor reliability metrics for advertiser-critical user journeys.
• Mentor engineers and provide technical leadership across multiple teams to ensure reliability is integrated into product roadmaps.

Requirements

• Must be based in the UK, the Netherlands, or Ireland.
• 8+ years of experience in Site Reliability Engineering or Infrastructure Engineering operating large-scale distributed systems.
• Deep understanding of distributed systems, networking, Linux, and cloud-native architectures.
• Strong programming skills in Go, Python, or similar languages.
• Proven experience designing highly available systems with strong operational practices.
• Strong understanding of observability systems including metrics, logging, tracing, and alerting.

Nice to have

• Experience supporting advertising technology platforms or other large-scale revenue-critical systems.
• Familiarity with Kubernetes, Kafka, ClickHouse, Spark, Flink, or BigQuery.
• Experience supporting machine learning inference or recommendation systems at scale.
• Experience partnering with Product and Data Science organizations.

Culture & Benefits

• Global benefit programs covering workspace, professional development, and caregiving support.
• Private medical, dental, and vision benefits.
• Flexible vacation policy and paid volunteer time off.
• Generous paid parental leave and family planning support.
• Mental health and coaching benefits.
• Personal retirement savings account with matching contributions.