Senior Site Reliability Engineer

We ship fast, but we don’t ship sloppy. SREs at CertifyOS own the full lifecycle of what they support — from infrastructure design and deployment automation through observability, incident response, and postmortems. We use AI-assisted tooling aggressively to reduce toil and accelerate troubleshooting, which raises the floor on the problems we tackle — not an excuse to reduce rigor. If you do your best work reacting to incidents, this probably isn’t the right fit. If you do your best work preventing them, we should talk.

Healthcare provider data infrastructure is a distributed systems problem at scale. Hundreds of upstream integrations, inconsistent data sources, and evolving workloads all introduce operational complexity and reliability risk.

Reliability and observability at scale. You’re operating a platform hundreds of integrations depend on. How do you maintain uptime, reduce alert fatigue, and build actionable observability across GKE and Cloud Run without drowning in noise? Meaningful SLIs, error budgets, and data quality signals — not just p99 latency.

Scaling infrastructure efficiently. As platform usage grows, infrastructure costs and operational complexity grow with it. You’ll improve autoscaling behavior, resource utilization, and workload efficiency across cloud-native distributed systems.

Incident response and operational maturity. Production incidents are inevitable; operational chaos is optional. You’ll own incident response processes, root cause analysis, escalation workflows, and runbooks — and make hard problems not happen again.

Infrastructure automation and developer velocity. You’ll build and maintain Infrastructure as Code, CI/CD pipelines, and operational tooling that reduce manual work and improve engineering productivity without sacrificing reliability.

Reliability engineering for data platforms. Uptime isn’t enough — you need to know when a provider record is stale, a pipeline is lagging, or a workload is behaving unexpectedly. You’ll instrument data freshness and infrastructure health, not just service uptime.

5+ years in SRE, DevOps, Platform Engineering, or Infrastructure Engineering — operating production systems at scale where your infrastructure is someone else’s dependency and failures have real downstream consequences

Track record of improving reliability end-to-end: you’ve debugged hard production problems, made them not happen again, and built the alerting to prove it

Strong Linux systems administration, incident response, and root cause analysis skills

Comfort influencing operational standards and mentoring teams on reliability practices

Deep hands-on experience with GCP — GKE, Cloud Run, and containerized workloads at scale

Experience building and maintaining Infrastructure as Code with Terraform and/or Pulumi

Fluency across deployment patterns and the judgment to know when each fits: rolling deployments, blue/green, canary — and the rollback story for each

Experience with autoscaling, resource optimization, and infrastructure efficiency for distributed systems

Experience managing infrastructure security, secrets, and access controls in regulated or security-conscious environments

Strong understanding of Golden Signals monitoring — latency, traffic, errors, saturation — and how to make them actionable rather than noisy

Experience designing SLIs, SLOs, error budgets, alerting strategies, dashboards, and escalation workflows

Hands-on experience with observability platforms: Google Cloud Monitoring, Datadog, Grafana, Prometheus, or similar

Strong sense of data platform health: lineage, freshness, and correctness matter as much to you as throughput

Experience building and maintaining CI/CD pipelines using GitHub Actions or similar

Scripting or programming fluency in Python, Bash, Go, or similar — you reduce toil through code, not process

Experience working with Git workflows and modern software delivery practices

Strong written and verbal communication — you can explain an operational risk to an engineer and a product manager in the same conversation

Experience operating systems handling sensitive data or PII in regulated or compliance-adjacent environments

Experience operating large-scale distributed systems or microservices architectures

Familiarity with healthcare, credentialing, or health-tech environments

Experience leveraging AI-assisted observability or incident response tooling

Familiarity with NodeJS, TypeScript, Java, or React application stacks

GCP (GKE, Cloud Run, BigQuery, Cloud Monitoring) · Terraform / Pulumi · Docker / Kubernetes · GitHub Actions / Cloud Build · Prometheus / Grafana / Datadog · Python / Bash / Go · Sentry · Snyk · SonarQube · Jira / Slack