Opportunity

Endeavour has an exciting opportunity for someone passionate about sustainability and eager to be part of an innovative company that’s on a journey to transform the world’s infrastructure. We are seeking a Director of Global IT DevOps & AI Infrastructure to take full ownership of how technology is built, deployed, secured, and scaled across the organization. This role is part of the support team that services the entire our Endeavour ecosystem and contributes to the overall health and success of the organization. This role goes beyond traditional IT. You will define and lead the end-to-end lifecycle of AI-powered digital products - from early-stage prototypes built in rapid-development environments to fully productionized, secure, and globally scalable platforms. You will serve as the bridge between innovation and execution, ensuring that ideas don’t stall in experimentation but are operationalized into resilient, enterprise-grade systems - while also building and leading the teams, financial models, and integration strategies required to sustain long-term growth.

The Director of Global IT DevOps & AI Infrastructure needs to be agile, professional, and comfortable in a rapidly changing environment. The right person is trustworthy with confidential information, highly organized, self-motivated, has excellent communication skills, can think strategically, and works equally as well independently as with a team.

Endeavour is highly selective about the people we bring on board because our ecosystem depends on it. Change happens quickly here, and we must maintain a strong team of honest, communicative, collaborative, open-minded, strategic, reliable, and driven team members. We seek ultra-creatives and superstar performers with self-awareness, a sense of humility, and a hunger to make a positive impact in the world.

Endeavour offers flexibility and endless growth opportunities to those who can harness their skills and talents and identify how and where to use them to add value. Our support team is the heart of the ecosystem. We’re a diverse group of bright, passionate, dedicated people, working together to make a real difference.

Are you ready to join the journey?

Key Responsibilities

Include but are not limited to: DevOps Ownership & Productionization of AI Systems

• Lead the DevOps Strategy: Own the end-to-end strategy including CI/CD pipelines, infrastructure-as-code (IaC), automated testing, and release management across all environments.
• Standardize Development Pathways: Design and enforce a standardized path from prototype to staging to production, specifically for AI-generated applications, low-code/no-code platforms (e.g., Lovable), and internal experimentation environments.
• Establish Frameworks: Drive versioning, monitoring, rollback, and observability across both AI and traditional applications.
• Implement Scalable Deployment Patterns: Utilize containers, serverless architectures, and microservices to support rapid iteration without sacrificing stability.

AI Platform Scaling & Lifecycle Management

• Manage the AI Lifecycle: Architect prompt engineering environments, model orchestration, API integrations, and validation pipelines.
• Evolve Prototypes: Define the pathway for AI prototypes to become internal tools, client-facing applications, and public-facing digital platforms.
• Establish Governance: Build frameworks for model usage, cost control, performance monitoring, and output reliability.
• Partner for Success: Collaborate with stakeholders to ensure AI solutions are production-ready, auditable, and aligned with business goals.

Cloud Architecture & Infrastructure Engineering

• 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 Complianc