Staff CI/CD and Cloud Infrastructure Engineer

Location: San Diego, CA Job Type: Full-Time Salary Range: $175,000 - $185,000 Position Overview We are looking for a Staff CI/CD & Cloud Infrastructure Engineer to own and evolve our build pipelines, deployment workflows, and cloud infrastructure. You will be responsible for ensuring that software — spanning Python, C/C++, and CUDA on Linux — is built, tested, versioned, and deployed reliably across both AWS cloud environments and a fleet of complex embedded instruments operated in our central lab facility. This is a senior hands-on role for an engineer who thrives at the intersection of DevOps automation, cloud infrastructure management, and release engineering. You will design and maintain CI/CD pipelines, manage complex AWS infrastructure as code, and ensure full traceability from source commits through builds, tests, artifacts, and deployments. You will work cross-functionally with firmware, application, and HPC engineers to keep the entire delivery pipeline fast, reliable, and observable. Key Responsibilities CI/CD & Build Engineering Design, 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 reliability Cloud 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 requirements On-Premises HPC & Hybrid Infrastructure Provision, 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 decisions Experiment Data Management & Pipelines Design 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 requirements Deployment & Release Engineering Own 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 parity Logging, Observability & Traceability Implement 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 incidents AI-Augmented DevOps Integrate 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 reliability Qualifications Education: BS/MS in Computer Science or Engineering Required Experience & Technical Skills 7+ 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 pipelines Programming & Build Systems Proficiency 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 languages Cloud & Infrastructure Deep 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 governance Observability & Traceability Experience with logging and monitoring stacks (Prometheus,Grafana, Loki, ELK, or CloudWatch)Understanding of build and artifact traceability practicesExperience with structured logging and distributed tracing concepts Preferred 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.