AI & Digital Workplace Engineer

Digital Workplace Platform Engineering

• Engineer and operate Microsoft Entra ID: conditional access, group and identity governance, SSO / SAML / OIDC integrations, hybrid identity (Entra Connect), Privileged Identity Management (PIM), and B2B / guest access governance.
  • Own identity lifecycle automation (Joiner / Mover / Leaver) and access governance across the global workforce.
  • Own endpoint management across Windows (Intune) and macOS (Jamf or equivalent MDM): policy, compliance, provisioning, and device performance.
  • Resolve complex M365 service issues across Exchange Online, Teams, SharePoint, and OneDrive that affect day-to-day productivity.
• Design, implement, and optimize digital workplace services to be scalable, reliable, secure, and compliant; use service-health metrics to remove bottlenecks and improve resilience and scalability.
  • Review and influence technical designs to meet performance standards, security requirements, and engineering best practice.

Operational Excellence, Service Management & Continual Improvement

• Lead complex incident response and blameless post-mortems; implement corrective actions that prevent recurrence.
  • Apply structured problem management — root-cause analysis, documented findings, and durable fixes over workarounds.
  • Drive Continual Service Improvement using ticket trends and service data to identify, implement, and measure improvements.
  • Build and maintain a knowledge base of known issues, runbooks, and resolution steps to reduce reliance on tribal knowledge and lower escalation volume into the service desk.
• Lead or contribute to the evaluation, implementation, and ongoing administration of the enterprise ITSM platform (Cherwell).
  • Apply NIST CSF 2.0 functions to assess risk, inform service-design decisions, and communicate risk posture in a common language with cybersecurity and senior leadership.
  • Champion automation, monitoring, and standardized engineering practices across the digital workplace.

AI-Enabled Digital Workplace Engineering & Practice Foundation

• Lead the engineering of AI capabilities embedded in productivity and collaboration platforms (Microsoft 365 Copilot and equivalents, third-party AI assistants, custom AI integrations).
  • Configure, integrate, and govern AI features across the digital workplace stack, balancing capability with security, privacy, and licensing constraints.
  • Build and maintain AI-driven workflows that automate or augment routine knowledge work across the enterprise.
  • Serve as the principal AI engineering authority for Enterprise IT — set AI tooling architecture, integration patterns, and operational standards for the broader IT organization.
  • Develop and maintain reusable AI capabilities — prompt libraries, AI-integrated workflows, reference patterns — and continuously evaluate the AI tooling landscape, recommending additions, replacements, or sunsets.
  • Author Architectural Decision Records (ADRs) for significant AI engineering decisions, preserving rationale, alternatives, and trade-offs for future engineering and audit review.

IT Automation & Internal AI Adoption

• Design and build AI-driven automation for IT itself — service desk augmentation, log analysis assistance, documentation generation, knowledge retrieval, and routine task automation.
  • Lead the technical aspects of IT's “AI-first” adoption — making sure IT staff have, use, and benefit from AI tools in their daily work.
  • Build and maintain shared AI capabilities, prompts, and workflows the IT team can leverage.
  • Measure and report on AI adoption and impact across the IT organization, in partnership with the workforce AI adoption and enablement program.
  • Operate technical telemetry that informs the broader AI adoption scorecard reported to IT leadership.

AI Governance, Security & Compliance Partnership

• Partner with the cybersecurity governance / GRC and IT compliance functions to operationalize AI usage policy — data handling, model selection, access controls, and acceptable use — at the platform engineering layer.
  • Implement and maintain technical controls that enforce AI policy at the digital workplace platform layer: tenant configuration, conditional access, data loss prevention, sensitivity labeling, and AI feature gating.
  • Maintain a living technical inventory of AI tools in use across the enterprise (sanctioned, conditionally permitted, prohibited) including data flows, integration surfaces, and applied controls. This inventory is the technical foundation that underpins the enterprise's EU AI Act Article 4 literacy evidence.
  • Operate technical detection and remediation for shadow-AI usage in coordination with GRC; surface adoption patterns and risks so curriculum and policy stay in step with reality.
  • Ensure AI integrations meet security, privacy, and licensing requirements; flag risks early in the integration design phase rather than at deployment.
  • Track and absorb adjacent regulatory and framework developments — NIST AI Risk Management Framework, ISO/IEC 42001, US state-level AI mandates — that affect technical implementation choices.

AI Fluency & Enablement Across IT

• Provide hands-on technical coaching to IT staff on applying AI to their specific engineering and operations work — prompt engineering, AI-assisted runbook authoring, AI-augmented troubleshooting, agentic patterns where appropriate.
  • Maintain a community of practice around AI usage in IT — sharing patterns, learnings, and pitfalls. It is the technical complement to the business-facing workforce AI adoption effort; the two run parallel and reinforce each other.
  • Serve as the go-to engineering resource for AI questions across the IT organization — the technical authority the rest of IT calls when an AI-related design decision needs an expert opinion.
  • Author and maintain technical reference material, playbooks, and ADRs that document AI engineering decisions and patterns for reuse across the team.
  • Cook up a demonstration of how to apply AI to a specific IT challenge, and provide guidance on best practices.