Infrastructure Architect

Description

Local candidates preferred.

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.