Senior DevOps Engineer – Observability & AI Ops

Rocket Lab

Littleton (CO)

On-site

USD 114,000 - 157,000

Full time

3 days ago

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Benefits offered by this job

Equity grant

Employee Stock Purchase Program

Health insurance

Paid time off

Job summary

Rocket Lab, a leading space company, is hiring a Senior DevOps Engineer I in Littleton, CO. You will build and optimize the observability platform, integrating telemetry across AWS/GCP, and driving reliability for mission-critical systems.

You will work with Space Systems teams to improve monitoring, dashboards, and incident response. You’ll partner with engineering to define SLIs/SLOs, implement durable instrumentation, and enhance alerting while contributing to AI-powered automation in CI/CD

Qualifications

Bachelor’s degree in Computer Science, Software Engineering, or other technical discipline.
5+ years of experience in DevOps, SRE, or related infrastructure discipline.
Hands-on experience operating production observability and monitoring platforms.
Experience with AI/ML technologies and AI-driven automation systems.
Experience with AWS and GCP cloud services.
Experience with Terraform and Git-based workflows.
U.S. citizenship is required.

Responsibilities

Build, operate, and continuously improve the observability stack (Grafana, Grafana Mimir, kube-prometheus-stack, Grafana Alloy).
Design scalable metrics collection, ingestion, retention, and query patterns for Kubernetes/cloud workloads.
Develop and maintain Grafana dashboards for engineering and leadership.
Design, tune, and maintain alerting and notification workflows.
Define meaningful SLOs/SLIs and monitoring standards with teams.
Improve observability coverage by identifying telemetry gaps and enhancing instrumentation.
Integrate AWS CloudWatch/CloudTrail telemetry for visibility and security monitoring.
Manage observability infrastructure via Terraform, Git, and CI/CD pipelines.
Drive data-driven reliability improvements and dashboard adoption.
Troubleshoot monitoring/alerting issues across AWS/GCP environments.
Collaborate with development teams to bake observability into pipelines.
Design and implement AI agents to detect and troubleshoot testing failures.
Build AI-powered quality automation that spans CI/CD across programs.