Staff Site Reliability Engineer

Team Overview

At TransUnion, this role will report to a DevOps Director. The Site Reliability Engineering team drives reliability strategy, elevates engineering standards, and owns some of the most complex and consequential work on the platform.

Role Overview And Core Responsibilities

• Technical Leadership & Strategic Influence
  - Recognized expert across multiple systems; actively contributes to architectural and strategic decisions around major platform components.
  - Leads research, testing, implementation, and continuous improvement for new systems and tooling.
  - Performs complex, high-impact work including capacity planning, load testing, and security improvements.

• Operational Excellence & On-Call
  - Fully participates in the team’s on-call rotation;
  - Models calm, effective, and blameless incident response;
  - Serves as a significant technical contributor during major incidents and problem resolution;
  - Plans and leads high-risk maintenance events with minimal to no customer impact.

• Standards & Team Elevation
  - Elevates team standards through new tooling, processes, procedures, and effective communication;
  - Capable of stepping in to lead and represent the team — a trusted resource during transitions or coverage gaps;
  - Sets new professional benchmarks in technical quality, engineering culture, and cross-functional collaboration.

Required Knowledge And Experiences

• Cloud Architecture, Site Reliability Engineering, Platform Engineering, or related fields — with a proven track record of designing and delivering at enterprise scale.

• Deep, hands-on expertise with Google Cloud Platform (GCP) and Kubernetes (K8s) — running high-volume, high-availability workloads with 99.999% reliability targets.

• Mastery of CI/CD pipeline architecture — designing end-to-end delivery systems that are fast, safe, and built for scale.

• Expert-level command of monitoring, observability, and alerting platforms (e.g., Datadog, Prometheus, Grafana, PagerDuty) — you define what good looks like.

• Advanced networking knowledge — including VPCs, subnets, DNS, load balancing, firewall rules, VPNs, private service connect, and hybrid connectivity patterns across cloud and on-prem environments.

• Strong proficiency in scripting and automation (e.g., Python, Bash, Go) — building the tools and workflows that eliminate toil and accelerate delivery.

• Hands-on experience designing and integrating AI/ML-powered solutions into cloud-native platforms — including familiarity with LLM orchestration, vector databases, model serving infrastructure, and AI observability — with the ability to evaluate emerging tools and translate them into reliable, production-grade capabilities.