Senior SRE: AI-First Cloud & Reliability

Evidently; San Francisco (CA); Remote; USD 200,000 - 250,000; Full time

Job summary

Evidently is seeking a Senior Systems Engineer to own reliability across our production systems, including the SMART on FHIR platform and AI inference pipelines. You will set SLOs, build dashboards, run blameless postmortems, and partner with leadership on operational decisions to prevent fires before they start.

You will also design scalable, secure cloud infrastructure on GCP, manage CI/CD pipelines, and ensure observability and security across data and AI components.

Qualifications

• 8+ years in SRE, infrastructure, or DevOps with ownership of reliability.
• Defined and defended SLOs and used error budgets to guide decisions.
• Led serious production incidents and wrote durable postmortems.
• Strong experience with GCP services (GKE, Cloud Run, AlloyDB, Pub/Sub, IAM).
• Fluent in Python; proficient Bash scripting for automation.
• Familiarity with AI infra and LLM inference serving is a plus.

Responsibilities

• Own reliability of production systems, define SLOs/SLIs, and set error budgets.
• Lead incident response, triage, communicate clearly, and drive durable fixes.
• Proactively identify reliability risks via capacity planning and chaos tests.
• Build runbooks and on-call practices; make on-call humane and effective.
• Design and maintain cloud infrastructure on Google Cloud Platform.

Skills

SRE leadership

Incident response

SLOs and error budgets

GCP expertise

Python scripting

Bash scripting

Kubernetes / GKE

Observability & monitoring

Tools

GCP

Terraform

Pulumi

Kubernetes

OpenTelemetry

BigQuery

Job description

Evidently is seeking a Senior Systems Engineer to own reliability across our production systems, including the SMART on FHIR platform and AI inference pipelines. You will set SLOs, build dashboards, run blameless postmortems, and partner with leadership on operational decisions to prevent fires before they start.

You will also design scalable, secure cloud infrastructure on GCP, manage CI/CD pipelines, and ensure observability and security across data and AI components.