Infrastructure Engineer

• Define and maintain the AI governance operating model spanning M365 Copilot, Copilot Studio (custom agents/copilots), Copilot Cowork, and third-party/internal AI solutions.
• Establish guardrails, approval workflows, and risk-tiering for AI use cases, agent publishing, and grounding-data access.
• Translate evolving AI regulations (EU AI Act, NIST AI RMF, sector-specific banking/financial guidance) and internal policy into enforceable technical controls.
• Own configuration and lifecycle management of the Microsoft Purview suite as the primary compliance control plane: Data Loss Prevention (DLP) — including Copilot-aware policies, Information Protection — sensitivity labels, encryption, and label-based access enforcement, Insider Risk Management, Communication Compliance, Audit (Standard/Premium) and unified audit logging for Copilot interactions, Compliance Manager — assessments, improvement actions, and control scoring.
• Implement and operate Data Security Posture Management (DSPM) for AI to monitor AI/Copilot usage, risky prompts, oversharing, and sensitive-data exposure.
• Manage adjacent compliance tooling: Microsoft Defender for Cloud Apps, Entra ID Conditional Access and entitlement/access reviews, SharePoint Advanced Management (restricted content discovery, access controls), and Microsoft Priva for privacy risk and subject-rights management.
• Design the enterprise sensitivity-label taxonomy and auto-classification model (trainable classifiers, exact data match, sensitive information types).
• Ensure classification drives Copilot grounding boundaries so AI responses respect least-privilege and need-to-know.
• Remediate oversharing and "data sprawl" that exposes content to Copilot semantic indexing.
• Define and enforce retention and deletion policies and labels across M365 workloads, including Copilot prompts, responses, and agent transcripts.
• Govern records management, disposition review, and defensible deletion in alignment with legal and regulatory retention schedules.
• Operate Microsoft Purview eDiscovery (Premium) and legal hold processes, ensuring Copilot interactions and AI-generated content are discoverable, preservable, and exportable for litigation and regulatory requests.
• Partner with Legal on holds, custodian management, search, and review workflows.
• Lead a team of infrastructure and compliance engineers; set technical direction, standards, and automation (PowerShell, Graph API, Microsoft Graph Data Connect, Sentinel/Logic Apps for control automation).
• Build monitoring, alerting, and reporting dashboards for AI governance KPIs and audit readiness.
• Drive incident response for AI/data compliance events and remediation.
• Serve as the primary technical liaison to Risk, Privacy, Legal, Security, and Audit on all AI governance matters.
• Produce executive-level reporting on AI compliance posture, control effectiveness, and regulatory readiness.

Senior Infrastructure Engineering Manager – AI

• Provide technical and customer service support for district courtroom and office workstations, mobile devices, network infrastructure, AV infrastructure and district production servers both remotely and on-site.
• Analyze, troubleshoot, and resolve IT Service Desk tickets, AV systems, telephone calls, and support request emails while maintaining a high standard of customer service.
• Install, maintain, upgrade, configure, monitor, patch, and secure District IT equipment.
• Consult and collaborate with local, district, state, and other court customers on technology innovation and improvement projects.
• Provide personalized training on courtroom and office technology hardware, software, and AV systems, both in person and remotely.
• Deploy, manage, and inventory standard workstations, software applications, storage and backup systems, and server configurations; create documentation and manage identity and access.
• Track, document, organize, locate, and inventory IT assets per Branch financial policies.

IT Infrastructure Engineer

• Lead or participate in high level technical concepts spanning technology and business
• Develop specifications for complex infrastructure systems, design and test solutions
• Contribute to the testing of business, application and technical infrastructure requirements
• Drive solutions to reduce recovery
• Review and analyze solutions for cloud security, secrets management and key rotations
• Design, code, test, debug and document programs using Agile development practices
• Design complex system upgrades
• Resolve troublesome trends as they develop
• Develop a long range plan designed to resolve problems and prevent them from recurring
• Direct the daily risk and control flow of operations, focusing on policies, procedures and work standards to ensure success
• Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals

Lead Infrastructure Engineer – Middleware MQ

• Own the rollout and operational management of AI-assisted development tools across engineering (e.g., Cursor, Copilot, Claude Code)
• Define and implement access controls, license management, and usage policies that satisfy SOC2/ISO 27001 requirements
• Build cost tracking and reporting so leadership has visibility into AI tool spend and usage patterns across the org
• Reduce friction for engineers adopting these tools while maintaining security and auditability
• Partner with teams across the org to identify, build, and support internal AI applications such as RAG pipelines, agents, and automation workflows
• Evaluate and recommend tooling, frameworks, and patterns based on what teams actually need
• Define where IaaS’s responsibility ends and consuming teams’ begins – this boundary doesn’t exist yet; you’ll help draw it
• Advise on data governance policies for LLM usage, including what data can go into which models, where outputs are stored, and how audit trails are maintained
• Ensure AI infrastructure and tooling meets existing SOC2 and ISO 27001 controls and can be evidenced in audits
• Provide leadership with clear, regular reporting on AI adoption, cost, risk, and usage across the org
• Stand up and manage AI/ML infrastructure, primarily on GCP (Vertex AI) within OpenVPN’s existing environment
• Design the Terraform modules and IaC patterns for AI infrastructure that follow the team’s existing conventions (e.g., Atlantis-driven GitOps workflows)
• Build visibility into AI/ML infrastructure costs and implement controls (spot instances, auto-scaling policies, idle resource cleanup) consistent with how compute costs are managed elsewhere
• Evaluate build-vs-buy decisions for AI/ML infrastructure components and managed services with an eye toward operational fit within existing patterns

Infrastructure Engineer – AI Platform

• The Infrastructure Engineer will work on cross functional teams to build scalable infrastructure for our government -- designing, implementing, and delivering services that millions of Americans depend on.
• As a Senior Infrastructure Engineer, you may be responsible for technical leadership of platform infrastructure projects supporting dev teams and large-scale systems with a strong focus on automation, organization, and communication.
• Your work enables application development teams to run effectively in the cloud to deliver users a modern experience.
• You will be responsible for delivering on client requirements as well as providing long-term oversight and vision to help shape future work.
• Your strong cross-functional communication skills will complement your technical leadership skills to provide the highest value for government systems.

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