This role pays more than
85%
of similar roles. Most pay
$126,800–$214,500
— the shaded band above.
At the midpoint, this role pays about
$222k
versus about
$171k
for comparable roles.
Based on 240 similar postings.
Employer
About Anduril Industries
Anduril Industries is a defense technology company that builds advanced hardware and software systems for national security, including autonomous drones, surveillance systems, and the Lattice AI command platform.
Anduril Industries currently has
1697 open roles
on FindRole.
Listed pay typically runs
$146,000–$194,000
across 1504 roles with salary data.
Staff DevOps Engineer
The Staff DevOps Engineer joins the CorpTech Platform team to establish the reliability architecture for systems supporting business and manufacturing operations. This role focuses on designing and operating observability infrastructure, including metrics, distributed tracing, and structured logging, while managing deployment systems such as canary analysis and automated rollbacks. The engineer will define SLO frameworks, identify systemic risks, and develop reliability patterns specifically for AI-enabled systems to manage non-deterministic behavior. Key responsibilities include leading incident response for multi-system failures and setting production-readiness standards across the organization. Required technical skills include proficiency in Go, Python, or Rust, along with deep expertise in Kubernetes, cloud platforms like AWS, GCP, or Azure, and networking. The role addresses the challenge of scaling reliability as a core platform property rather than an individual effort within complex corporate infrastructure.
What does a DevOps Engineer earn?
Median $126800 from 89 postings across 26 companies.
Design and manage the reliability architecture for production environments including observability, deployment systems, and incident management.
Build and operate an enterprise-scale observability platform featuring metrics, distributed tracing, and structured logging.
Develop release-safety mechanisms such as canary analysis, automated rollbacks, and progressive rollout systems.
Establish and govern SLO frameworks to make reliability measurable for engineering teams and leadership.
Identify systemic risks and implement automation to eliminate entire classes of failures rather than patching symptoms.
Define production-readiness standards and review processes to embed reliability into the software development lifecycle.
Lead incident response for complex multi-system failures and drive durable, systemic improvements from post-incident reviews.
Develop reliability patterns specifically for AI-enabled systems, including monitoring for model behavior drift and degradation.
What we're looking for
10+ years of experience in site reliability engineering, production engineering, infrastructure engineering, or a related discipline at an architecture or platform-wide scope.
Demonstrated experience designing and owning reliability infrastructure such as observability platforms, deployment systems, or incident management tooling at scale.
Deep technical fluency in distributed systems, Kubernetes, cloud platforms (AWS, GCP, or Azure), networking, and storage.
Proficiency in systems programming languages including Go, Python, Rust, or equivalent for building production infrastructure and automation.
Demonstrated experience defining SRE standards and influencing adoption across engineering teams without formal authority.
Track record of leading incident response for complex failures and converting findings into systemic infrastructure improvements.
Degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience.
U.S. Person status is required to access export controlled data.