Job DescriptionJob Overview:McDermott is seeking an experienced
Technology Manager, Artificial Intelligence Infrastructure to lead the strategy, architecture, deployment, governance, and operations of enterprise AI infrastructure platforms and services. This role will be responsible for building and managing the foundational technologies that enable artificial intelligence, machine learning, generative AI, intelligent automation, and AI-driven operations across the organization.
The successful candidate will work closely with Infrastructure, Cloud, Security, Data & Analytics, Enterprise Architecture, and business stakeholders to establish a secure, scalable, resilient, and cost-effective AI ecosystem that supports current and future business objectives.
This position combines technical leadership, operational excellence, and strategic planning to accelerate McDermott's AI transformation journey.
ResponsibilitiesKey Tasks and Responsibilities:AI Infrastructure Strategy & Architecture- Develop and execute the enterprise AI infrastructure roadmap aligned with business and technology objectives.
- Design and oversee scalable AI platform architectures across on-premises, hybrid, and cloud environments.
- Establish standards, governance, and best practices for AI infrastructure services.
- Collaborate with Enterprise Architecture and Security teams to ensure compliance and alignment with corporate technology standards.
- Evaluate emerging AI technologies and identify opportunities for adoption.
AI Platform Engineering- Lead implementation and operations of enterprise AI platforms, including:
- Azure AI Services
- Azure OpenAI Service
- Microsoft Copilot Technologies
- AI Agents and Agentic AI platforms
- Machine Learning platforms
- Vector databases and RAG architectures
- GPU and accelerated compute environments
- Design infrastructure supporting AI model training, inference, and deployment workloads.
- Establish AI workload lifecycle management practices.
Cloud & Infrastructure Management- Manage AI infrastructure across Azure and hybrid environments.
- Oversee provisioning, capacity planning, performance optimization, and lifecycle management.
- Implement Infrastructure-as-Code (IaC) using Bicep, Terraform, and automation frameworks.
- Ensure high availability, resilience, disaster recovery, and business continuity for AI platforms.
- Manage cloud consumption, cost optimization, and resource governance.
AI Operations (AIOps) & Automation- Drive implementation of AIOps capabilities across infrastructure operations.
- Leverage observability platforms such as ServiceNow ITOM, Azure Monitor, and SolarWinds.
- Develop self-healing and automated remediation capabilities.
- Utilize AI and automation to improve operational efficiency and service delivery.
- Define KPIs and operational metrics for AI service management.
Security, Governance & Risk Management- Ensure AI solutions comply with cybersecurity, privacy, legal, and regulatory requirements.
- Partner with Information Security teams to implement secure AI architectures.
- Define governance frameworks for responsible AI usage.
- Implement controls for data protection, access management, model governance, and compliance monitoring.
- Conduct risk assessments and mitigation planning for AI infrastructure platforms.
Leadership & People Management- Lead and mentor a team of AI infrastructure engineers and platform specialists.
- Foster a culture of innovation, automation, continuous improvement, and operational excellence.
- Develop technical talent through coaching, training, and career development.
- Manage vendor relationships, support contracts, and technology partnerships.
- Lead cross-functional project teams delivering strategic AI initiatives.
Technical SkillsAI & Machine Learning- Azure OpenAI Service
- Azure AI Foundry
- Microsoft Copilot Studio
- AI Agents & Agentic Frameworks
- Retrieval-Augmented Generation (RAG)
- Vector Databases
- Large Language Models (LLMs)
- Machine Learning Operations (MLOps)
Cloud & Infrastructure- Microsoft Azure
- Azure Kubernetes Service (AKS)
- Azure Landing Zones
- Azure Networking
- Azure Storage
- Azure Virtual Machines
- Hybrid Cloud Architectures
Automation & DevOps- Bicep
- Terraform
- GitHub Enterprise
- GitHub Actions
- PowerShell
- Python
- CI/CD Pipelines
Observability & IT Operations- ServiceNow ITOM
- Azure Monitor
- Log Analytics
- SolarWinds
- AIOps Platforms
- Performance Monitoring
- Event Management
Security & Governance- Microsoft Entra ID
- Azure Security Center / Defender
- Identity & Access Management
- Data Governance
- Compliance Controls
- Zero Trust Security Architecture
QualificationsEssential Qualifications and Education:- Bachelor's degree in Computer Science, Information Technology, Engineering, or related discipline.
- Master's degree preferred.
- 10+ years of progressive experience in enterprise infrastructure, cloud, platform engineering, or technology operations.
- 5+ years leading technical teams and strategic technology initiatives.
- 3+ years of hands-on experience supporting AI, machine learning, or advanced analytics platforms.
- Experience managing large-scale enterprise cloud environments.
- Microsoft Certified: Azure Solutions Architect Expert
- Microsoft Certified: Azure AI Engineer Associate
- Microsoft Certified: Azure Administrator Associate
- Microsoft Certified: Security Engineer Associate
- Microsoft Certified: DevOps Engineer Expert
- HashiCorp Terraform Associate
- ITIL Foundation Certification
Leadership Competencies- Strategic Thinking
- Technology Vision & Innovation
- Executive Communication
- Organizational Leadership
- Vendor & Stakeholder Management
- Financial & Budget Management
- Team Development & Coaching
- Change Leadership
- Risk Management
- Operational Excellence
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