About this role

This is a remote position.

Project Description

Support secure, reliable, and compliant operation of cloud-hosted research applications, agentic AI systems, scientific SaaS platforms, and production services.
Work across GCP, AWS, cloud containers, AI/ML models, MCP servers, APIs, scientific databases, and third-party SaaS platforms.
Support scientists, developers, IT, cybersecurity, networking, data teams, architecture, and vendors in transitioning research prototypes into secure, repeatable, production-ready services.

Administer GCP/AWS cloud projects, IAM, service accounts, networking, storage, compute, quotas, and SaaS environments.
Operate Cloud Run, Docker containers, registries, DNS, TLS, load balancing, and Google Cloud IAP.
Manage identities, RBAC, SSO, OAuth, service accounts, machine-to-machine authentication, secrets, API keys, tokens, and certificates.
Maintain approved AI agents, MCP servers, tools, integrations, data sources, permissions, and credentials.
Maintain Dockerfiles, container images, Python/application dependencies, registries, runtime configurations, and rollback procedures.
Monitor logs, metrics, traces, alerts, dashboards, health checks, API limits, model/tool failures, token usage, cloud costs, and service availability.
Maintain CI/CD pipelines and infrastructure-as-code, including source control, security scanning, testing, approvals, and deployment traceability.
Perform incident triage, escalation, root-cause analysis, backup/recovery, disaster recovery, and service continuity.
Manage incidents, service requests, problems, and changes using ServiceNow and Jira.
Support vulnerability remediation, patching, security investigations, audits, threat modeling, and risk assessments.
Identify shadow AI services, unmanaged integrations, unapproved MCP servers, and overprivileged identities.
Create operational runbooks, technical documentation, and lifecycle/ownership documentation.
Help transition scientist-managed prototypes into secure, supportable production deployments.

Mandatory Requirements
Bachelor’s degree in Computer Science, Information Systems, Engineering, Technology, or related field.
3+ years of experience in systems/cloud administration.
Production administration experience with GCP, AWS, Azure, or comparable cloud platforms.
Hands-on experience with:
Linux
Docker/containers
Python environments
APIs
Networking, DNS, and TLS
IAM, SSO, OAuth, service accounts
Secrets management
Serverless/container orchestration such as Cloud Run or Kubernetes
Knowledge of:
CI/CD
Infrastructure as Code
Monitoring and observability
Incident management
Backup/recovery
Patching
Vulnerability remediation
Experience with ServiceNow and Jira.
Strong troubleshooting, documentation, communication, and cross-functional collaboration skills.
Preferred Skills
GCP IAP, Cloud Run, Secret Manager, Artifact Registry, Cloud Monitoring.
Vertex AI, Gemini, or other AI/ML platform administration.
Experience supporting GCP + AWS hybrid/multi-cloud environments.
Agentic AI, AI orchestration, MCP servers**, AI APIs, or model operations.
Scientific computing, bioinformatics, laboratory automation, multiomics, research data platforms, or scientific SaaS.
Container scanning, SBOM, software supply-chain security, data integrity, and auditability.
Cloud, systems engineering, ITSM, or cybersecurity certifications.

Systems Administrator