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Systems Administrator, Research AI & Applications
Job Description
We respectfully request that 3 rd parties refrain from contacting us regarding this posting. Systems Administrator, Research AI and Applications LABUR is partnering with a client to identify a Systems Administrator, Research AI and Applications to ensure the secure, reliable, and compliant operation of cloud-hosted research applications, agentic AI systems, and scientific SaaS platforms. This role supports systems integrating cloud infrastructure, containers, AI models, Model Context Protocol (MCP) servers, scientific databases, APIs, and third-party services. The administrator collaborates with scientists, developers, IT platform owners, cybersecurity, networking, data teams, and vendors to maintain pipeline and production services. Responsibilities Administer research applications and infrastructure across Google Cloud Platform, AWS, and scientific SaaS environments, including IAM, service accounts, networking, storage, compute, Cloud Run services, containers, registries, DNS, TLS certificates, load balancing, and Identity-Aware Proxy while maintaining separation across development, test, validation, and production environments. Maintain inventories of approved agents, MCP servers, tools, data sources, integrations, permissions, and credentials; update and support tooling for agentic AI frameworks and orchestration libraries. Manage user, group, service account, and machine-to-machine access using role-based access controls and least-privilege principles; rotate API keys, tokens, certificates, and credentials while eliminating hard-coded secrets. Maintain container images, Dockerfiles, base images, runtime configurations, registries, and pinned Python and application dependencies; monitor and remediate vulnerabilities, deprecations, and compatibility issues with documented rollback procedures. Operate CI/CD pipelines and infrastructure-as-code configurations with source control, peer review, testing, security scanning, deployment approvals, and rollback controls; help transition scientist-managed prototypes into documented, repeatable, and supportable production deployments. Maintain logs, metrics, traces, alerts, dashboards, and automated health checks covering availability, performance, errors, API limits, model and tool failures, token consumption, and cloud cost; create runbooks and support incident triage, escalation, root-cause analysis, backup, restoration, and disaster recovery. Record and manage incidents, service requests, changes, and operational work through ServiceNow and Jira with clear ownership, status, documentation, traceability, and escalation. Apply enterprise security, privacy, and change-control standards; maintain audit logs for administrative actions, system changes, user access, and agent tool calls; identify unmanaged integrations, unapproved MCP servers, shadow AI services, and overprivileged identities. Required Qualifications Bachelor's degree in computer science, information systems, engineering, technology, or a related field with at least 3 years of experience administering production systems in GCP, AWS, Azure, or a comparable cloud environment. Hands-on experience with Linux, containers, Docker, Python environments, APIs, networking, DNS, TLS, identity, secrets management, and serverless or container orchestration services such as Cloud Run or Kubernetes. Knowledge of IAM, SSO, OAuth, service accounts, machine-to-machine authentication, CI/CD, infrastructure as code, monitoring, incident management, backup, recovery, patching, and vulnerability remediation. Familiarity with ServiceNow for IT service management and Jira for work intake, backlog management, issue tracking, and operational work management. Strong troubleshooting, documentation, communication, and cross-functional collaboration skills. Preferred Qualifications Experience with Google Cloud IAP, Cloud Run, Secret Manager, Artifact Registry, Cloud Monitoring, Gemini, or Vertex AI, including multi-cloud systems spanning GCP and AWS. Familiarity with scientific computing, bioinformatics, laboratory automation, multiomics, research data platforms, or scientific SaaS; knowledge of container scanning, software bills of materials, supply-chain security, data integrity, and auditability. Relevant cloud, systems engineering, ITSM, or cybersecurity certifications are desirable. Compensation $50.00-$60.00/hr - Dependent on fit and experience.