Staff Site Reliability Engineer

levistraussandco; España; Presencial; EUR 120.000 - 180.000; Jornada completa

Descripción de la vacante

Levi Strauss & Co. in Spain seeks an exceptional Staff Site Reliability Engineer to own the reliability, scalability, and operability of our data and AI platforms.

You will lead with GCP expertise across multi-cloud environments to support the design of our iconic jeans and global operations. As a hands-on technical leader, you will reduce toil, improve observability, and define SLOs/SLIs, while mentoring junior engineers and partnering with Data, Security, and Product teams to embed reliability

Formación

• Master's degree in Computer Science, Engineering, or related field (or equivalent practical experience).
• 10+ years in SRE, DevOps, or Platform Engineering in large-scale production.
• Deep hands-on GCP experience (GKE, Cloud Run, BigQuery, Pub/Sub, GCS, Composer, Dataflow, Vertex AI).
• Terraform and Helm with GitOps (ArgoCD, Flux).
• Strong observability skills: tracing, logging, metrics, alerting (Cloud Monitoring, Datadog, Prometheus/Grafana).
• Experience defining/operating SLOs/SLIs/error budgets in production.
• Data security: IAM, encryption, secrets, network policies, compliance.
• Experience in multi-cloud (GCP + Azure).
• Ability to lead without authority.

Responsabilidades

• Define, instrument, and enforce SLOs, SLIs across platform services.
• Reduce MTTD/MTTR via observability, alerting, and runbook incident response.
• Lead blameless post-mortems and drive reliability improvements.
• Identify and reduce operational toil; maintain guardrails to keep toil under 50%.
• Build self-serve infrastructure for teams to provision and operate resources.
• Automate deployment pipelines and IaC workflows (Terraform, Helm, GitOps).
• Architect workloads across GCP (GKE, Cloud Run, BigQuery, Pub/Sub, etc.) and Azure.
• Design self-healing infra, auto-scaling, and capacity planning for high availability.
• Champion data security and governance: encryption, IAM, secrets, audit logs.
• Apply SRE to agentic AI workloads; define reliability for LLM/multi-agent systems.
• Partner with AI Platform teams to productionize pipelines with monitoring and drift detection.
• Drive adoption of AI-assisted operations tooling for observability and incident management.
• Lead and mentor junior/mid-level SREs; collaborate with cross-functional teams.
• Communicate platform health and reliability roadmap to technical and exec audiences.

Conocimientos

SRE experience

DevOps

Platform engineering

Leadership & mentoring

Communication with executives

Educación

Master's degree in Computer Science or related field

Herramientas

Terraform

Helm

GitOps (ArgoCD, Flux)

Cloud Monitoring

Datadog

Prometheus/Grafana

ArgoCD

Flux

Descripción del empleo

Job Location: Spain

Calling all originals: At Levi Strauss & Co., you can be yourself - and be part of something bigger. We're a company of people who like to forge our own path and leave the world better than we found it. Who believe that what makes us different makes us stronger. So add your voice. Make an impact. Find your fit - and your future.

We're seeking an exceptional Staff Site Reliability Engineer to join our Data & AI Platform Engineering team. In this role, you'll own and elevate the reliability, scalability, and operability of our enterprise data and AI platforms - the platforms that power everything from the design of our iconic jeans to the optimization of our global retail and supply chain.

As a hands-on technical leader, you'll embody the principles of Google's SRE discipline: eliminating toil, engineering for reliability, and building a culture of shared ownership between development and operations. This is a unique opportunity to shape how a legendary brand runs production at scale on Google Cloud Platform, with a growing multi-cloud footprint across GCP and Azure.

About the Job

Reliability & Incident Management

• Define, instrument, and enforce SLOs, SLIs, and error budgets across all platform services, ensuring alignment with business and product commitments
• Drive continuous reduction in MTTD and MTTR through improved observability, automated alerting, and runbook-driven incident response
• Lead blameless post-mortems and translate findings into durable reliability improvements, ensuring systemic issues are eliminated rather than patched

Toil Reduction & Automation

• Systematically identify, measure, and eliminate operational toil; track toil percentage per sprint and enforce guardrails to keep it below 50% of engineering capacity
• Build and maintain self-serve infrastructure capabilities - enabling product and data engineering teams to provision, scale, and operate their own resources safely and consistently
• Automate deployment pipelines, configuration management, and operational workflows using Infrastructure-as-Code principles (Terraform, Helm, GitOps)

Platform Engineering & Architecture

• Serve as the primary GCP subject matter expert - architecting and optimizing workloads across GKE, Cloud Run, BigQuery, Pub/Sub, GCS, Composer, Dataflow, and Vertex AI
• Lead multi-cloud architecture decisions across GCP and Azure, ensuring consistent security posture, cost efficiency, and operational practices across environments
• Design and implement self-healing infrastructure patterns , auto-scaling strategies, and capacity planning models to support high-availability data and AI platforms
• Champion data security and governance best practices - including encryption at rest and in transit, IAM least-privilege, secrets management, and audit logging

AI, Agentic Systems & Modern Observability

• Apply SRE principles to agentic AI workloads - defining reliability expectations for LLM-based and multi-agent systems, including latency SLOs, fallback patterns, and model observability
• Partner with AI Platform teams to productionize agentic pipelines with robust monitoring, drift detection, and rollback capabilities
• Drive adoption of AI-assisted operations tooling to enhance observability, anomaly detection, and predictive incident management

Leadership & Culture

• Guide and mentor junior and mid-level SREs - conducting code reviews, running reliability reviews, and elevating the team's engineering craft
• Collaborate cross-functionally with Data Engineering, Software Engineering, Security, and Product teams to embed reliability as a shared value from design through deployment
• Champion a culture of psychological safety, continuous learning, and reliability excellence
• Communicate platform health, risk posture, and reliability roadmaps clearly to both technical and executive audiences

About You

Required Qualifications

• Master's degree in Computer Science, Engineering, or related field (or equivalent practical experience)
• 10+ years of experience in Site Reliability Engineering, DevOps, or Platform Engineering, with a strong track record in large-scale production environments
• Deep, hands-on expertise in GCP - including GKE, Cloud Run, BigQuery, Pub/Sub, GCS, Composer, Dataflow, and Vertex AI
• Proficiency with Infrastructure-as-Code tools (Terraform, Helm) and GitOps workflows (ArgoCD, Flux)
• Strong command of observability tooling - distributed tracing, structured logging, metrics pipelines, and alerting platforms (e.g., Cloud Monitoring, Datadog, Prometheus/Grafana)
• Proven experience defining and operating against SLOs, SLIs, and error budgets in production environments
• Solid understanding of data security principles : IAM, encryption, secrets management, network policies, and compliance frameworks
• Experience with multi-cloud environments (GCP + Azure), including cross-cloud networking, identity federation, and cost governance
• Demonstrated ability to lead without authority - influencing engineers acr