AI Systems Engineer

WebMD•Yardley, PA

10d•$120,000 - $145,000•Hybrid

About The Position

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.

Requirements

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 PowerShell 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 NetApp; 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 ID (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 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 deployment
Experience authoring AI systems documentation: architecture diagrams, runbooks, security assessments, and governance policies
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 management
Familiarity with network security concepts including firewall policy, VPN administration, WAF configuration, and zero-trust network access models
Experience with endpoint management using Microsoft Intune or comparable MDM solutions

Nice To Haves

Certifications in VMware, Hyper-V, MCSE, MCSA, or AWS/Azure Solutions Architect are desirable
Certifications or coursework in AI/ML platforms, prompt engineering, or responsible AI are a plus
Experience with infrastructure-as-code tooling (Terraform, Bicep, or comparable) is advantageous
Familiarity with SIEM platforms (Microsoft Sentinel, Splunk, or similar) for security monitoring
Experience with acquisition IT integration: user provisioning, mailbox migrations, SSO federation, and directory consolidation

Responsibilities

Provide technical support to corporate business units and support their applications across the enterprise
Maintain the back-end IT infrastructure estate including servers, storage, UPS, and Hyper-V environments
Perform Windows Server upgrades, rebuilds, and OS lifecycle management
Manage and maintain security patches across server infrastructure on a defined cadence
Migrate data across cloud, hybrid, and on-premises environments with documented rollback plans
Administer and maintain Windows Server DNS including zone health, record lifecycle, replication, and conditional forwarding configurations
Build and maintain DR environments, runbooks, and failover/failback plans; participate in DR testing exercises
Work with or without formal SOPs; author and maintain runbooks and technical documentation as environments evolve
Proactively learn and document the environments of current and future acquired companies to enable smooth integration
Serve as a thought leader and architect new IDF/MDF configurations; identify opportunities to scale back or synergize infrastructure across the portfolio
Be comfortable with on-call schedules and respond to critical alerts in a timely and effective manner
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 governance
Architect 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
Integrate 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 pipelines
Conduct periodic AI connector and platform security assessments covering permission scopes, credential exposure, data residency, output validation, and prompt injection risk; document findings and drive remediation
Implement and maintain AI hardening controls: API gateway rate limiting, WAF rules for AI endpoints, session management, kill switch procedures, and anomaly monitoring via SIEM
Partner with business units to evaluate new AI tools and vendor platforms; perform pre-deployment security reviews and produce architecture documentation before production rollout
Maintain comprehensive documentation for all AI systems: architecture diagrams, security assessment reports, connector governance policies, and operational runbooks
Stay current with developments in enterprise AI platforms, MCP ecosystem tooling, and AI security best practices; translate emerging capabilities into actionable infrastructure improvements
Collaborate with legal, compliance, and security teams to ensure AI platform usage aligns with HIPAA, data privacy obligations, and organizational policy
Establish strong working relationships with corporate business units, the Operations team, IT leadership, and direct manager
Work cross-functionally to coordinate large-scale infrastructure efforts, migrations, and AI platform rollouts
Represent IT infrastructure and AI operations as a subject-matter expert in cross-team planning and architecture discussions
Communicate project status, risks, and decisions clearly to both technical and non-technical stakeholders