Infrastructure Architect

Role: Infrastructure Architect

Location: Dallas, TX(Hybrid)

Type: Contract

Job Summary

• We are seeking an experienced AI Platform Architect to lead the technical architecture, strategy, and evolution of enterprise AI platforms. This role will provide architectural leadership for large-scale AI and cloud platform initiatives, partnering with engineering, infrastructure, security, product, and business stakeholders to deliver scalable, resilient, and secure AI capabilities.
• The successful candidate will demonstrate deep expertise in cloud-native architectures, AI/ML platforms, distributed systems, and platform engineering, along with the ability to influence technical roadmaps and lead cross-functional initiatives.

Key Responsibilities

• Architecture Leadership
• Lead architecture and technical direction for enterprise AI platform capabilities, including:
• Enterprise Generative AI platforms
• Agentic AI platforms and agent runtime environments
• Model serving and inference infrastructure
• Prompt engineering, evaluation, and testing frameworks
• AI governance, risk management, and guardrails
• AI observability, monitoring, and operations
• Multi-cloud AI platform strategy and architecture
• Platform Architecture & Design
• Design, evaluate, and guide architecture across AI and cloud technologies such as:
• Red Hat OpenShift AI (RHOAI)
• Google Cloud Vertex AI
• Gemini models
• Azure AI Foundry
• Amazon Bedrock
• Anthropic Claude
• OpenAI services and models
• Cloud-native platform scalability and resiliency solutions
• Strategic Initiatives
• Lead and collaborate on initiatives involving:
• Capacity planning and performance optimization
• GPU infrastructure and platform strategy
• Large-scale NVIDIA-based AI infrastructure architectures
• Multi-region and multi-cloud resiliency
• Disaster recovery planning and cloud DR strategies
• Active-active platform architectures
• High availability and business continuity solutions

Required Qualifications:

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field; or equivalent combination of education and relevant experience.
• Minimum of 10 years of experience in software engineering, infrastructure engineering, systems architecture, or related technical disciplines.
• Minimum of 5 years of experience designing and implementing large-scale cloud-native platforms.
• Experience designing, deploying, and supporting highly available, mission-critical production systems.
• Experience with:
• Kubernetes and/or OpenShift
• Distributed systems architectures
• Public cloud platforms and cloud-native architectures
• AI/ML platforms and infrastructure
• API and integration platforms
• Data platforms and data-intensive applications
• Knowledge of:
• Generative AI systems and architectures
• Retrieval-Augmented Generation (RAG)
• Agentic AI frameworks and platforms
• Model serving and inference architectures
• MLOps practices and tooling
• Demonstrated ability to lead technical initiatives across multiple teams and stakeholders.
• Ability to work from or relocate to one of the following approved locations: San Francisco Bay Area, CA; Charlotte, NC; Dallas, TX; Phoenix, AZ; or New York, NY.

Preferred Qualifications:

• Experience with one or more major cloud providers, including AWS, Azure, or Google Cloud Platform.
• Experience architecting GPU-accelerated AI infrastructure.
• Experience implementing AI governance, security, risk management, and compliance controls.
• Experience building or supporting multi-region, highly resilient enterprise platforms.
• Relevant industry certifications in cloud, AI/ML, Kubernetes, or architecture disciplines.