DevOps Engineer

• Design, build, and operate Kubernetes platforms for secure, highly available, and scalable critical production services across hybrid and public-cloud environments
• Build infrastructure as code with Terraform using reusable modules, safe delivery workflows, and governed infrastructure changes
• Develop backend services, internal tools, and operational automation in Go, Python, or JavaScript/TypeScript
• Partner with engineering and product teams to translate workload requirements into pragmatic solutions for reliability, performance, capacity, security, and cost
• Improve the production lifecycle through CI/CD, deployment automation, progressive delivery, and clear operational ownership
• Define and evolve observability practices across metrics, logs, traces, alerting, and dashboards
• Participate in on-call, lead incident response, perform root-cause analysis, and drive blameless postmortems and corrective actions
• Establish reliability targets using SLIs, SLOs, error budgets, capacity planning, disaster-recovery testing, and resilience improvements
• Embed security and compliance into platform operations
• Apply AI-assisted and data-driven operational techniques to improve signal detection, reduce alert noise, accelerate root-cause analysis, and identify automation opportunities
• Contribute through code reviews, documentation, knowledge sharing, and mentorship
• Mentor and support team growth

Senior Site Reliability Engineer – Infra Ops

• Architect, implement, and maintain enterprise-grade cloud cost allocation, governance, and automated remediation systems
• Implement automated cost estimation, budget limits, and policy-as-code validation in CI/CD pipelines
• Develop internal tools, microservices, and event-driven automation for idle resource teardown, instance right-sizing, anomaly detection, and tag compliance
• Design and operate granular Kubernetes container cost allocation, bin-packing, and autoscaling strategies
• Build scalable pipelines and analytical models for cloud billing data using SQL and cloud data platforms
• Model, automate, and manage enterprise commitment lifecycles including Savings Plans, Reserved Instances, and Committed Use Discounts
• Engineer resilient architectures for Spot and preemptible workloads
• Establish telemetry linking infrastructure consumption metrics with business KPIs
• Lead recurring technical cost architecture reviews and provide optimization recommendations
• Mentor DevOps, SRE, and software engineers on financial engineering and sustainable cloud architecture

Senior DevOps Engineer – FinOps

• Build reliability features as productized code, including libraries, services, controllers, deployment safety guards, rate-limiters, circuit breakers, load-shedding adapters, and back-pressure controls
• Define and implement observability platforms with telemetry pipelines, SLIs/SLOs, error-budget policies, SDKs, CLIs, plugins, and release gates
• Build change-safety tooling using progressive delivery, automated rollback, release validation, reusable services/operators, and CI/CD integrations
• Develop resilience automation including fault-injection APIs, chaos experiments, traffic shadowing, and load/performance harnesses
• Create golden-path platform components using Terraform/Pulumi modules, Kubernetes operators, Helm charts, and reference microservice templates
• Develop incident-learning automation for context capture, timelines, action tracking, and systemic code fixes
• Write high-quality code in Go, TypeScript/Node.js, C#, or Java; design APIs, write tests, and ship iteratively
• Lead designs for distributed, multi-region services initially on Azure
• Partner with Staff/Principal peers across product and platform to align reliability standards and drive adoption
• Instrument systems, automate detection and response, and maintain actionable alerting
• Lead complex incidents, drive blameless learning, and implement systemic fixes
• Mentor senior engineers through design reviews, ADRs, and pair programming
• Drive strategic initiatives and define architectural best practices for Veeam’s global SRE function

Staff Site Reliability Engineer

• Own reliability and availability across colocation server fleets, on-premises lab clusters, cloud environments, and customer-facing platform services
• Provision and configure servers, operating systems, networking, storage, and hardware from bare metal through auto-scaling Kubernetes environments
• Lead capacity planning and hardware lifecycle management
• Track cloud spend to support FinOps and workload-placement decisions
• Drive provisioning, deployment, and operational changes through Terraform and/or Ansible
• Contribute to shared infrastructure-as-code modules for global SRE and data center services teams
• Build automation for host lifecycle management, fleet health checks, auto-remediation, self-service tooling, and networking automation
• Design and maintain monitoring, alerting, and service-level indicators using Prometheus/Grafana, DataDog, Splunk, or equivalent tools
• Contribute to AIOps-driven detection workflows
• Participate in an on-call rotation and resolve incidents from bare metal to application layer
• Produce root-cause analyses for P0/P1 incidents
• Support internal and external customer platform services, ensuring QoS and uptime commitments
• Document operational runbooks
• Partner with hardware and software teams on CI/CD, QA, HPC workloads, silicon development, and customer deployments

Senior Staff Site Reliability Engineer, AI Infrastructure

• Design, develop, troubleshoot, and debug software programs supporting a mature CI/CD pipeline
• Develop and maintain CI/CD pipelines
• Build tools to reduce errors and improve user experience
• Develop and maintain integrations with internal back-end systems
• Perform root cause analysis of production errors and resolve technical issues
• Develop observability tools for the end-to-end pipeline lifecycle
• Design procedures for system troubleshooting and maintenance
• Maintain common developer resources and continuously apply relevant security updates
• Apply intermediate subject matter expertise to solve common technical problems
• Provide analysis and recommendations for appropriate action
• Work independently within an established framework with moderate supervision

• Design, develop, troubleshoot, and debug software programs supporting a mature CI/CD pipeline
• Develop and maintain CI/CD pipelines
• Build tools to reduce errors and improve user experience
• Develop and maintain integrations with internal back-end systems
• Perform root cause analysis of production errors and resolve technical issues
• Develop observability tools for the pipeline lifecycle
• Design procedures for system troubleshooting and maintenance
• Maintain common developer resources and continuously apply relevant security updates
• Provide analysis and recommendations for appropriate action
• Work independently within an established framework with moderate supervision

• Define the model CI strategy for frontier models running on OpenAI custom silicon and integrated accelerator systems
• Build production CI/CD pipelines for functional regression, performance benchmarking, software stability, and release qualification
• Design test matrices across models, configurations, hardware generations, software components, and deployment environments
• Create performance baselines, regression detection, bisect and triage workflows, and failure ownership processes
• Establish GitOps practices for reproducible configuration, promotion, rollback, auditability, and environment consistency
• Shape monorepo architecture, dependency management, build and test boundaries, change validation, and developer workflows
• Develop orchestration, artifact management, caching, scheduling, observability, and capacity controls for accelerator-backed CI
• Partner with model, compiler, kernel, runtime, firmware, validation, and hardware teams to automate release-risk gates
• Improve CI reliability, speed, debuggability, and cost efficiency while maintaining production confidence

Software Engineer – DevOps

• Own the end-to-end data-center hardware quality and reliability loop for OpenAI’s 3P infrastructure and 1P current and next-generation platforms
• Build and govern the field-quality data model across telemetry, tickets, RMA/repair, failure analysis, firmware, configuration, supplier, and manufacturing genealogy
• Define AFR, ASR, DPPM, MTBF/MTTR, repeat-repair, NTF, repair-cycle-time, and forecast-versus-actual metrics with explicit denominators and uncertainty
• Provide fleet-level macro views and unit/FRU/cohort-level micro views; detect shifts and bound affected populations
• Lead systemic field-failure triage, containment, failure analysis, 8D/CAPA, risk assessment, corrective-action verification, and recurrence monitoring
• Develop cohort, life-data, reliability-growth, and spare-demand projections by product, FRU, supplier, configuration, geography, and age
• Partner with MQE and NPI to convert field mechanisms into manufacturing-test coverage, screening/stress profiles, diagnostics, control plans, DFR/DFS requirements, FMEA/FTA, mission profiles, FRU strategy, and qualification gates
• Verify whether upstream changes reduce field recurrence
• Define supplier/CM failure-analysis standards, field-data contracts, scorecards, escalation paths, and closure evidence
• Provide serviceability, TCO, and spares inputs without owning inventory execution or procurement
• Create executive decision packages covering population at risk, exposure, confidence, options, cost/risk, and recommendation
• Run the cross-functional reliability council and mentor 1P and 3P Field Quality Engineers as the team grows

Data Center Hardware Quality – Reliability Engineer

• Lead SRE across observability, incident management, load testing, performance engineering, cloud cost and capacity, and rollout infrastructure
• Lead and grow an existing team building and operating production platforms across application and infrastructure boundaries
• Build and operate metrics, logs, traces, and alerting capabilities
• Help teams establish meaningful SLOs and use production telemetry to diagnose problems and verify improvements
• Own incident tooling and practices, coordinate cross-team response, and turn incident reviews into engineering improvements
• Build and maintain load and failure-testing capabilities
• Validate critical paths under expected demand, quantify headroom, and test recovery and production readiness with service owners
• Lead deep engagements on SLOs and end-to-end performance
• Use profiling, telemetry, and load tests to identify bottlenecks and deliver improvements with service owners
• Review designs and production changes, debug difficult failure modes, and use AI coding tools to prototype and automate
• Coach engineers, develop technical leaders, manage performance, and hire against agreed needs
• Establish deliberate distributed collaboration, mentoring, and backup coverage
• Track rollout safety, recovery time, repeat incidents, critical-path latency/throughput, test coverage, and cost/capacity improvements
• Agree success measures and continuing ownership with partner teams

DevOps Engineer jobs in California

Senior Site Reliability Engineer – Infra Ops

Senior DevOps Engineer – FinOps

Staff Site Reliability Engineer

Senior Staff Site Reliability Engineer, AI Infrastructure

DevOps Engineer

DevOps Engineer

DevOps Engineer

Software Engineer – DevOps

Data Center Hardware Quality – Reliability Engineer

Engineering Manager – Site Reliability Engineering