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. Position Requirements: Infrastructure & Systems Administration Experience across the complete infrastructure stack: network, security, storage, hardware, and OS layerExpertise with Windows Server administration, configuration, upgrades, and lifecycle managementDeep expertise in PowerShell scripting for automation, provisioning, reporting, and systems managementExpertise in DNS and DHCP administration, including Windows Server DNS roles, zone management, conditional forwarding, split-brain DNS, and DNSSECExperience with enterprise backup tools including NetApp; building DR environments and failover plansProficiency with virtualization platforms: VMware and/or Hyper-VExperience managing and maintaining security patches across server and application estatesExperience migrating data across cloud, hybrid, and on-premises environmentsAbility to plan, organize, and document complex system maintenance activities; configure systems consistent with institutional policies and proceduresComfortable with on-call schedules and response to critical alerts in a timely manner Cloud & Productivity Platforms Experience with Google Workspace administration (user lifecycle, OU management, GAM scripting)Experience with Google Cloud Platform (GCP) infrastructure and servicesExperience with Microsoft Office 365 administration including licensing, Exchange Online, and complianceExperience with Microsoft Azure including Entra ID (formerly Azure AD), Conditional Access, PIM, and Azure resource managementFamiliarity with setting up and configuring applications with Azure SSO or Google SSO (SAML, OIDC, OAuth 2.0) AI Systems Engineering & Operations 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 environmentsExperience 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 controlsAbility to design and enforce AI connector governance policies: scope management, permission auditing, credential lifecycle, and connector access reviewsExperience performing AI platform security assessments covering permission scopes, data flows, output validation pipelines, prompt injection defenses, and HITL (Human-in-the-Loop) controlsFamiliarity with AI hardening principles: model access controls, rate limiting, WAF integration, API gateway configuration, session controls, and kill switch hierarchies for AI systemsExperience configuring and monitoring SIEM detection rules for AI platform activity and anomaly detectionUnderstanding of responsible AI deployment including data residency requirements, privacy-by-design, audit logging, and regulatory alignment (HIPAA, GDPR as applicable)Ability to evaluate new AI tools and platforms against enterprise security standards prior to production deploymentExperience authoring AI systems documentation: architecture diagrams, runbooks, security assessments, and governance policies Security & Compliance Knowledge of applicable data privacy practices, laws, and regulations (HIPAA, SOC 2, GDPR fundamentals)Experience with identity and access management (IAM) tooling: Entra ID, Active Directory, SAML/OIDC federation, MFA enforcement, and privileged access managementFamiliarity with network security concepts including firewall policy, VPN administration, WAF configuration, and zero-trust network access modelsExperience with endpoint management using Microsoft Intune or comparable MDM solutions Certifications & Nice-to-Have Certifications in VMware, Hyper-V, MCSE, MCSA, or AWS/Azure Solutions Architect are desirableCertifications or coursework in AI/ML platforms, prompt engineering, or responsible AI are a plusExperience with infrastructure-as-code tooling (Terraform, Bicep, or comparable) is advantageousFamiliarity with SIEM platforms (Microsoft Sentinel, Splunk, or similar) for security monitoringExperience with acquisition IT integration: user provisioning, mailbox migrations, SSO federation, and directory consolidation Roles & Responsibilities Infrastructure Operations Provide technical support to corporate business units and support their applications across the enterpriseMaintain the back-end IT infrastructure estate including servers, storage, UPS, and Hyper-V environmentsPerform Windows Server upgrades, rebuilds, and OS lifecycle managementManage and maintain security patches across server infrastructure on a defined cadenceMigrate data across cloud, hybrid, and on-premises environments with documented rollback plansAdminister and maintain Windows Server DNS including zone health, record lifecycle, replication, and conditional forwarding configurationsBuild and maintain DR environments, runbooks, and failover/failback plans; participate in DR testing exercisesWork with or without formal SOPs; author and maintain runbooks and technical documentation as environments evolveProactively learn and document the environments of current and future acquired companies to enable smooth integrationServe as a thought leader and architect new IDF/MDF configurations; identify opportunities to scale back or synergize infrastructure across the portfolioBe comfortable with on-call schedules and respond to critical alerts in a timely and effective manner AI Systems Engineering & Governance Own the deployment, configuration, and ongoing administration of enterprise AI platforms including Anthropic Claude (claude.ai, Claude API, Claude Code) and Google Gemini; manage platform accounts, access policies, and usage governanceArchitect and manage the enterprise MCP server infrastructure: deploy and maintain MCP server instances, configure tool and connector registries, manage connector lifecycle (onboarding, auditing, deprecation), and enforce data flow and permission policies across connectors Collaboration & Stakeholder Engagement Establish strong working relationships with corporate business units, the Operations team, IT leadership, and direct managerWork cross-functionally to coordinate large-scale infrastructure efforts, migrations, and AI platform rolloutsRepresent IT infrastructure and AI operations as a subject-matter expert in cross-team planning and architecture discussionsCommunicate project status, risks, and decisions clearly to both technical and non-technical stakeholders Salary range: $120,000 - $145,000 Bonus Eligible: This position is also eligible for a discretionary company bonus, based upon business results. Benefits: Employees in this position are eligible to participate in the company sponsored benefit programs, including the following within the first 12 months of employment: Health Insurance (medical, dental, and vision coverage)Paid Time Off (including vacation, sick leave, and flexible holiday days)401(k) Retirement Plan with employer matchingLife and Disability InsuranceEmployee Assistance Program (EAP)Commuter and/or Transit Benefits (if applicable)Eligibility for specific benefits may vary based on job classification, schedule (e.g., full-time vs. part-time), work location and length of employment.