AI Systems Engineer

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Position Overview

The AI & Systems Engineer is a hybrid infrastructure and AI operations role responsible for managing the full enterprise IT stack while also architecting, deploying, securing, and governing AI systems across the organization. This role serves as the primary technical owner for AI platform integrations—including large language models, MCP servers, and connector ecosystems—alongside traditional systems administration responsibilities covering Windows Server, cloud platforms, network infrastructure, and enterprise security.

The ideal candidate bridges deep infrastructure expertise with hands-on AI engineering, ensuring AI systems are deployed with rigor, properly hardened, and tightly integrated with existing enterprise identity and security controls.

• Experience across the complete infrastructure stack: network, security, storage, hardware, and OS layer
• Expertise with Windows Server administration, configuration, upgrades, and lifecycle management
• Deep expertise in Power Shell scripting for automation, provisioning, reporting, and systems management
• Expertise in DNS and DHCP administration, including Windows Server DNS roles, zone management, conditional forwarding, split-brain DNS, and DNSSEC
• Experience with enterprise backup tools including Net App; building DR environments and failover plans
• Proficiency with virtualization platforms: VMware and/or Hyper-V
• Experience managing and maintaining security patches across server and application estates
• Experience migrating data across cloud, hybrid, and on-premises environments
• Ability to plan, organize, and document complex system maintenance activities; configure systems consistent with institutional policies and procedures
• Comfortable with on-call schedules and response to critical alerts in a timely manner

• Experience with Google Workspace administration (user lifecycle, OU management, GAM scripting)
• Experience with Google Cloud Platform (GCP) infrastructure and services
• Experience with Microsoft Office 365 administration including licensing, Exchange Online, and compliance
• Experience with Microsoft Azure including Entra  (formerly Azure AD), Conditional Access, PIM, and Azure resource management
• Familiarity with setting up and configuring applications with Azure SSO or Google SSO (SAML, OIDC, OAuth 2.0)

• Hands-on experience deploying, configuring, and administering large language model (LLM) platforms including Anthropic Claude (claude.ai, Claude API, Claude Code) and Google Gemini across enterprise environments
• Experience architecting and administering MCP (Model Context Protocol) server infrastructure: deploying MCP server instances, configuring tool registries, managing connector ecosystems (Airtable, Atlassian, Google Drive, Gmail, and others), and integrating MCP servers with enterprise identity and access controls
• Ability to design and enforce AI connector governance policies: scope management, permission auditing, credential lifecycle, and connector access reviews
• Experience performing AI platform security assessments covering permission scopes, data flows, output validation pipelines, prompt injection defenses, and HITL (Human-in-the-Loop) controls
• Familiarity with AI hardening principles: model access controls, rate limiting, WAF integration, API gateway configuration, session controls, and kill switch hierarchies for AI systems
• Experience configuring and monitoring SIEM detection rules for AI platform activity and anomaly detection
• Understanding of…