Overview Staff Engineer, CI/CD & Cloud InfrastructureLocation: San Diego, CAJob Type: Full-TimeSalary Range: $ 175,000 - $185,000Responsibilities CI/CD & Build EngineeringDesign, build, and maintain CI/CD pipelines using GitHub Actions or similar platformsManage build systems for Python, C/C++, and CUDA codebases on LinuxIntegrate build tools (CMake, Make, pip, setuptools) into automated pipelinesImplement robust versioning, tagging, and artifact management strategiesEnsure full traceability of builds, test results, and artifacts from commit to deploymentManage Docker-based build environments including base images, caching, and reproducibilityMaintain and optimize build performance, parallelism, and reliabilityCloud Infrastructure (AWS)Architect and manage complex AWS infrastructure including:IAM roles, policies, and access managementStorage services (S3, EBS, EFS) with tiered lifecycle policiesDatabases (RDS, DynamoDB, or similar) with backup and failover strategiesData workflow and pipeline engines (Step Functions, Airflow, or similar)Compute services (EC2, ECS, EKS, Lambda) scaled to workload requirementsImplement infrastructure as code using TerraformManage Kubernetes clusters and Helm charts for containerized workloadsDesign for scalability, high availability, and disaster recoveryManage cost optimization, resource tagging, and infrastructure governanceSupport multi-account and multi-region strategies as neededFamiliarity with Azure and GCP for secondary or hybrid requirementsrequirementsOn-Premises HPC & Hybrid InfrastructureProvision, configure, and manage on-premises Linux HPC nodes used for secondary and tertiary data processingDefine infrastructure-as-code (Terraform, Ansible, or similar) for reproducible HPC node provisioning and configurationManage high-speed networking infrastructure between instruments, HPC nodes, and storage (configuration, monitoring, troubleshooting)Implement and manage shared storage systems (NFS, parallel filesystems, or similar) accessible to both local HPC and cloud computeDesign and operate hybrid burst-to-cloud infrastructure — provision and manage AWS compute resources that extend local HPC capacity on demandCollaborate with the data pipeline team to ensure infrastructure meets throughput, latency, and reliability requirementsManage OS patching, driver updates, and GPU runtime environments across HPC nodesMonitor HPC cluster health, utilization, and capacity to inform scaling decisionsExperiment Data Management & PipelinesDesign and operate data ingestion pipelines for high-volume experiment data from lab instrumentsImplement tiered storage strategies (hot/warm/cold) to balance accessibility, performance, and costDeploy and manage search infrastructure (Elasticsearch/OpenSearch) to make experiment data universally discoverable and queryableBuild data cataloging and metadata tagging systems so datasets are well-organized and self-describingIntegrate visualization tools (Grafana, Kibana, or similar) to enable engineers and scientists to explore and analyze experiment dataDesign data lifecycle policies including retention, archival, and compliance requirementsEnsure data pipelines are reliable, idempotent, and observable with clear error handling and retry logicWork with engineering and science teams to define data schemas, access patterns, and query requirementsDeployment & Release EngineeringOwn deployment workflows for software delivered to embedded instruments in our central labManage release processes for a small number of complex, high-value lab-operated instrumentsDesign deployment strategies that account for rollback, validation, and minimal downtimeCoordinate versioned releases across multiple software components and dependenciesSupport development, staging, and production environment parityLogging, Observability & TraceabilityImplement centralized log collection and aggregation across cloud and on-site systemsDeploy and manage observability tooling (Prometheus, Grafana, Loki, CloudWatch, or similar)Ensure structured, searchable logging with clear correlation across servicesBuild dashboards and alerting for infrastructure health, pipeline status, and deployment stateEstablish traceability standards linking builds, tests, artifacts, and deploymentsSupport diagnostics and post-mortem analysis for production incidentsAI-Augmented DevOpsIntegrate agentic AI tools into CI/CD workflows to automate code review, test generation, and pipeline troubleshootingEvaluate and deploy AI-powered assistants for infrastructure management, incident response, and operational tasksDesign guardrails and human-in-the-loop controls for AI-driven automation in production environmentsStay current with the rapidly evolving landscape of AI-augmented development and DevOps toolingChampion adoption of agentic AI across engineering workflows to accelerate delivery and improve reliabilityQualifications Education:BS/MS in Computer Science or EngineeringRequired:Experience & Technical Skills7+ years of experience in DevOps, CI/CD, or cloud infrastructure rolesStrong, hands-on Linux expertise (administration, debugging, performance tuning)Deep experience designing and operating CI/CD pipelines (GitHub Actions preferred)Proven experience managing complex AWS infrastructure at scaleStrong knowledge of Docker including multi-stage builds, registries, and orchestrationExperience with infrastructure as code using TerraformExperience with Kubernetes and Helm for container orchestrationSolid understanding of versioning strategies, artifact management, and release engineeringExperience integrating agentic AI into DevOps workflows and CI/CD pipelinesProgramming & Build SystemsProficiency in Python and shell scripting for automation and toolingAbility to read, debug, and build C/C++ and CUDA applications on LinuxExperience integrating build systems (CMake, Make) into CI pipelinesFamiliarity with package management and dependency resolution across languagesCloud & InfrastructureDeep AWS experience across IAM, networking (VPC, security groups), storage, compute, and database servicesExperience managing on-premises Linux HPC infrastructure alongside cloud resourcesExperience designing for high availability, failover, and disaster recoveryExperience with data pipeline and workflow orchestration tools (Step Functions, Airflow, or similar)Experience with search and indexing platforms (Elasticsearch, OpenSearch, or similar)Understanding of tiered storage strategies and data lifecycle managementKnowledge of cost management, tagging strategies, and infrastructure governanceObservability & TraceabilityExperience with logging and monitoring stacks (Prometheus, Grafana, Loki, ELK, or CloudWatch)Understanding of build and artifact traceability practicesExperience with structured logging and distributed tracing conceptsPreferred:Experience deploying software to embedded or lab-operated instrumentsExperience with high-speed networking (InfiniBand, RDMA, or 10/25/100GbE) in HPC environmentsExperience with CUDA build toolchains and GPU-accelerated workloadsFamiliarity with Azure or GCP in addition to AWSExperience in regulated or reliability-sensitive environmentsExperience with GitOps workflows and progressive delivery strategiesFamiliarity with secrets management (Vault, AWS Secrets Manager)We are an equal opportunity employer. We thrive on diversity and collaboration.#J-18808-Ljbffr