SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 191,000 - 253,000 / annual
Anduril Industries is a defense technology company building AI-powered military systems. CorpTech Platform is the internal engineering force multiplier that powers Anduril's corporate and manufacturing systems, including CorpOS (Finance and Growth operations) and ArsenalOS (hardware enterprise backbone).
This Staff SRE role sets the reliability architecture for systems running Anduril's business and manufacturing operations. You are not responding to tickets; you decide how production works: observability, safe deployments, incident management, and reliability scaling. You own the infrastructure and mechanisms that make reliability a platform property rather than dependent on individual heroics.
The role carries broad organizational reach. You will influence how software engineering teams across CorpTech Platform build and operate systems, set production-readiness standards, and make infrastructure decisions affecting every service in the portfolio. You bring deep systems expertise and judgment about which reliability investments matter most at each growth stage.
Key responsibilities include:
- Set reliability architecture for CorpTech Platform's production environment: observability infrastructure, deployment systems, incident management, capacity planning, and failure-domain isolation
- Design and operate the observability platform (metrics, distributed tracing, structured logging, alerting, dashboarding) giving engineering teams real production visibility at scale
- Own deployment infrastructure and release-safety mechanisms (progressive rollout, canary analysis, automated rollback, deployment gates) enabling fast shipping without production-stability risk
- Define and govern SLO frameworks making reliability measurable and actionable, creating shared language between SRE, product engineering, and leadership for trade-off decisions
- Identify systemic reliability risks across the platform and drive infrastructure or automation investments eliminating entire failure classes
- Establish production-readiness standards and review processes that engineering teams adopt during design and pre-launch, embedding reliability into the development lifecycle
- Lead incident response for complex, multi-system failures and drive post-incident processes producing durable systemic improvements
- Develop reliability patterns for AI-enabled systems, including monitoring for model behavior drift, non-deterministic output degradation, and graceful fallback under novel failure modes
- Provide technical direction to SRE and infrastructure engineers, facilitate cross-team architecture decisions, and represent reliability concerns in platform-level planning
- Drive capacity planning, cost optimization, and performance engineering for the platform's critical paths and shared infrastructure
REQUIREMENTS:
- 10+ years of experience in site reliability engineering, production engineering, infrastructure engineering, or closely related discipline, including experience operating at architecture or platform-wide scope
- Demonstrated experience designing and owning reliability infrastructure that multiple engineering teams depend on (observability platforms, deployment systems, incident management tooling) at meaningful scale
- Deep technical fluency across distributed systems, container orchestration (Kubernetes), cloud platforms (AWS, GCP, or Azure), networking, storage, and failure modes specific to each layer
- Proficiency in systems programming languages (Go, Python, Rust, or equivalent) used for building production infrastructure, tooling, and automation
- Demonstrated experience defining SRE standards, production-readiness frameworks, or operational maturity models and influencing adoption across engineering teams without formal authority
- Track record of leading incident response for complex, multi-system failures and converting post-incident findings into infrastructure investments that prevent recurrence
- Proven ability to work independently through ambiguity, define reliability strategy without top-down direction, and sequence investments against competing organizational demands
- Excellent written and verbal communication skills, with ability to influence senior engineers, engineering leadership, and cross-functional partners on infrastructure and reliability decisions
- Degree in Computer Science, Information Systems, Engineering, or related technical field, or equivalent practical experience
- U.S. Person status required (position needs to access export controlled data)
PREFERRED QUALIFICATIONS:
- Experience designing or operating observability platforms (Datadog, Grafana, Prometheus, OpenTelemetry) at organizational scale
- Experience building deployment and release-safety infrastructure (canary systems, progressive delivery, feature flagging, automated rollback)
- Experience with reliability engineering for AI-enabled or ML-serving systems
- Familiarity with frontier AI tooling, AI coding assistants, and AI-enabled software development workflows
- Experience in hyper-growth startup-like environments scaling reliability practices alongside rapid engineering growth
- Familiarity with enterprise systems domains (ERP, MES, WMS, CRM, finance systems, manufacturing systems)
- Eligible to obtain and maintain a U.S. Secret security clearance
