AI Systems Engineer

AI & Systems Engineer Position at WebMDWebMD is the most recognized and trusted brand of health information and the leading provider of health information services, serving consumers, physicians, healthcare professionals, employers and health plans through our public and private online portals and WebMD the Magazine. The WebMD Health Network includes WebMD, Medscape, MedicineNet, eMedicine, RxList, theheart.org and Medscape Education. Our consumer portals and mobile health applications provide engaging, relevant and credible health and wellness information, personalized health assessment tools and access to online communities. WebMD is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.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 RequirementsInfrastructure & Systems AdministrationExperience 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 mannerCloud & Productivity PlatformsExperience 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 & OperationsHands-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 policiesSecurity & ComplianceKnowledge 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 solutionsCertifications & Nice-to-HaveCertifications 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 consolidationRoles & ResponsibilitiesInfrastructure OperationsProvide 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 mannerAI Systems Engineering & GovernanceOwn 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 connectorsIntegrate AI platforms and MCP servers with enterprise IAM controls (Entra ID / Azure AD SSO, Conditional Access, MFA) to ensure AI system access is governed through standard identity pipelinesConduct periodic AI connector and platform security assessments covering permission scopes, credential exposure, data residency, output validation, and prompt injection risk; document findings and drive remediationImplement and maintain AI hardening controls: API gateway rate limiting, WAF rules for AI endpoints, session management, kill switch procedures, and anomaly monitoring via SIEMPartner with business units to evaluate new AI tools and vendor platforms; perform pre-deployment security reviews and produce architecture documentation before production rolloutMaintain comprehensive documentation for all AI systems: architecture diagrams, security assessment reports, connector governance policies, and operational runbooksStay current with developments in enterprise AI platforms, MCP ecosystem tooling, and AI security best practices; translate emerging capabilities into actionable infrastructure improvements