> Markdown version of [/jobs/ext/4525118-infrastructure-architect](https://www.wearedevelopers.com/jobs/ext/4525118-infrastructure-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Infrastructure Architect

- **Company:** Kasmo Inc
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computing Platforms, Systems Engineering, Microsoft Azure, Big Data, Cloud Computing, Cloud Engineering, Cloud Foundry, Information Systems, Disaster Recovery, Distributed Systems, OpenShift, Performance Tuning, OpenAI, Azure Machine Learning, Software Engineering, Systems Architecture, AI Infrastructure, Google Cloud, Cloud Platform System, System Availability, Prompt Engineering, Multi-Cloud, Generative AI, Agentic-AI, AI Platforms, Kubernetes, Information Technology, Amazon Bedrock, Data Management, Machine Learning Operations, Hardware Infrastructure, Claude, Google Gemini
- **Published:** November 2, 2026
- **Apply:** https://www.careerbuilder.com/job-details/infrastructure-architect-nc--c0905e49-0b1c-4a29-ac38-8e7a6a0f08b2

## About the Role

Software Engineering, Architectural Services, Artificial Intelligence (AI), Cloud Computing, Leadership, Technical Strategy, Distributed Computing, Cross-Functional, Systems Engineering, Cloud Architecture, 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.

## Description

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