Director of Global IT DevOps & AI Infrastructure

Optimize Cloud Environments: Own global cloud infrastructure (primarily Microsoft Azure) to ensure high availability, security, compliance, and horizontal scalability. - Design for Data: Architect infrastructure that supports data-intensive workloads, spatial systems, and AI-driven applications. - Build Resilient Systems: Ensure infrastructure is capable of supporting global users, partners, and mission-critical operations. AI Security & Enterprise Governance

Secure AI Usage: Establish secure enterprise environments with data isolation, sandboxing, role-based access controls (RBAC), and secure API orchestration. - Protect Critical Assets: Define governance policies that protect proprietary infrastructure designs and sensitive client/operational data. - Ensure Compliance: Stay ahead of evolving standards regarding AI usage, data privacy, and enterprise risk management. Team Leadership & Organizational Development

Build and Lead High-Performing Teams: Recruit, develop, and scale global DevOps, cloud engineering, and AI infrastructure teams, fostering a culture of accountability, innovation, and operational excellence. - Define Operating Models: Establish clear roles, workflows, and performance expectations across distributed teams, contractors, and external partners. - Mentor and Develop Talent: Provide hands-on leadership, coaching, and career development for technical team members, ensuring long-term capability growth. - Cross-Functional Leadership: Act as a key partner to product, engineering, and business leaders to align technical execution with company priorities. Budget Ownership & Financial Management

Own the Technology Budget: Develop and manage the global IT DevOps and cloud infrastructure budget, including forecasting, cost optimization, and vendor management. - Optimize Cloud & AI Spend: Implement cost governance strategies across cloud platforms, AI tooling, and third-party services to ensure efficient scaling. - Vendor & Partner Management: Evaluate, negotiate, and manage relationships with technology vendors, SaaS providers, and infrastructure partners. - ROI-Driven Decision Making: Ensure all infrastructure and AI investments are aligned with measurable business outcomes and scalability goals. Integration Strategy & Systems Architecture

Lead Enterprise Integration Strategy: Define and oversee integration architecture across internal systems, third-party platforms, and partner ecosystems. - API & Data Ecosystem Ownership: Ensure seamless interoperability between AI platforms, ERP/supply chain systems, data visualization tools, and spatial technologies. - Enable Scalable Data Flows: Architect reliable, secure, and real-time data pipelines that support both operational systems and AI-driven insights. - Reduce Technical Fragmentation: Standardize integration patterns, tools, and governance to minimize redundancy and improve system cohesion across the organization. Global Collaboration & Asset Ownership

Platform Enablement: Architect identity, access, and collaboration systems for a globally distributed workforce, ensuring seamless interaction between internal teams, partners, clients, and vendors. - Digital Infrastructure Ownership: Take full command of domain registries, DNS architecture, SSL lifecycle management, global routing, and web infrastructure. - Performance Assurance: Ensure all digital assets are secure, performant, and scalable across regions. ## Education and Experience

7+ years in IT DevOps, AI infrastructure or cloud engineering

3+ years of leadership experience

Bachelor’s or Master’s degree in Information Technology, Computer Science, Business Management, or a related field. - Proven DevOps & Scaling Leadership: Experience owning DevOps and infrastructure in environments scaling from startup to enterprise ($100M–$1B+), with a track record of taking products from MVP to production-grade systems. - Team Leadership Experience: Demonstrated success building and leading high-performing global engineering or infrastructure teams in fast-paced environments. - Financial & Budget Ownership: Experience managing technology budgets, optimizing cloud spend, and aligning investments with business outcomes. - Deep Technical Expertise: Strong, hands-on experience with Microsoft Azure (or equivalent cloud platforms), CI/CD pipelines, containers, IaC, networking, DNS, and distributed systems. - Integration & Systems Thinking: Experience managing complex integrations across APIs, data visualization platforms, and ERP/supply chain technologies. - Strategic & Hands-On Operator: Capable of operating at an executive, architectural level while remaining comfortable rolling up your sleeves to build systems from scratch. ## Specific Skills / Abilities

AI Ecosystem Fluency: Proven ability to operationalize LLMs, AI platforms, and rapid-development (low-code/no-code) ecosystems within an enterprise, deeply understanding AI reliability, evaluation, and scaling challenges. - Strategic & Hands-On Operator: Capable of operating at an executive, architectural level while remaining comfortable rolling up your sleeves to build systems from scratch. - Mission Alignment: Deeply motivated by applying technology and AI to solve real-world challenges in global water and energy infrastructure.