Cloud Infrastructure & AI Operations Engineer

Pioneer Circuits Inc.•Santa Ana, CA

8h•Onsite

About The Position

The Cloud Infrastructure & AI Operations Engineer designs, implements, and manages secure, scalable cloud infrastructure that supports advanced manufacturing and next-generation technology initiatives. Working cross-functionally with engineering, operations, and innovation teams, you will architect and operate mission-critical systems in GovCloud that power Industry 4.0 capabilities. You’ll work closely with our AI and Automation Engineers on deploying across departments AI/ML workloads, automating infrastructure, and supporting compliance with FedRAMP, CMMC, and ITAR requirements—all while contributing to the evolution of secure, intelligent systems. This is an opportunity to move beyond traditional systems administration and work on building the backbone for autonomous systems, intelligent monitoring, and modern defense technology. You’ll play a key role in enabling automation, improving operational performance, and driving data-informed decision-making across the organization through collaboration with stakeholders at all levels.

Requirements

Strong expertise in infrastructure automation, container orchestration, and serverless architectures
Experience managing cloud infrastructure, preferably in AWS GovCloud or similar secure cloud environments
Proven experience deploying and operating AI/ML workloads in production
Hands-on experience with Infrastructure as Code tools (e.g., Terraform, CloudFormation) and GitOps practices
Proficiency in scripting and development using Python, Bash, or PowerShell
Experience with AI-assisted monitoring, predictive analytics, or intelligent log analysis tools
Understanding of AI/ML infrastructure requirements (e.g., GPU compute, data pipelines, model serving)
Ability to use intelligent alerting and predictive tools for proactive system management
Working knowledge of FedRAMP, CMMC, ITAR, or similar regulatory frameworks (Preferred)
Experience implementing zero-trust architecture, identity management, and data protection controls
Understanding of secure AI/ML pipelines and responsible AI practices in regulated environments
Strong analytical and troubleshooting skills with a focus on automation and continuous improvement
Ability to document complex systems and communicate effectively with both technical and non-technical stakeholders
Experience supporting large-scale distributed systems with a focus on observability, reliability, and performance
Strong collaborative mindset with ability to work effectively across technical and business teams
Excellent communication skills for partnering with cross-functional stakeholders
Must be a U.S. citizen or lawful permanent resident

Nice To Haves

Certifications such as AWS Solutions Architect or Security Specialty, Certified Kubernetes Administrator (CKA), Terraform Associate, or relevant security certifications (e.g., CISSP, Security+)
Experience with AI/ML platforms such as MLflow, Kubeflow, SageMaker, or similar tools
Familiarity with edge computing, including edge AI deployment, IoT platforms, or hybrid cloud-edge architectures
Experience managing content delivery networks (CDNs), API gateways, or containerized web applications at scale

Responsibilities

Design, deploy, and manage secure GovCloud environments, including but not limited to Microsoft and AWS, supporting AI/ML workloads, containerized applications, and serverless architecture
Implement and maintain AI-assisted monitoring, predictive analytics, and intelligent automation platforms for proactive infrastructure management
Deploy and orchestrate containerized AI models using ECS, EKS, or similar platforms with a focus on scalability and resilience
Build and maintain CI/CD pipelines for both infrastructure and machine learning model deployment using GitOps workflows
Ensure continuous compliance with FedRAMP, CMMC, ITAR, and other defense-grade security frameworks
Implement zero-trust network architecture, identity federation (IAM, SSO), and data protection controls
Manage secure AI pipeline workflows, including data classification, encryption (at rest and in transit), and audit logging
Conduct security assessments and implement automated compliance monitoring
Develop and maintain infrastructure as code using Terraform, CloudFormation, or CDK for repeatable, version-controlled deployments
Create automation workflows using Python, Bash, or PowerShell to improve system performance and efficiency
Implement configuration management at scale using Ansible, Systems Manager, or similar tools
Build self-healing infrastructure with automated remediation and intelligent alerting
Deploy distributed tracing, centralized logging, and real-time monitoring across hybrid cloud environments
Utilize AI-assisted tools for anomaly detection, log analysis, and endpoint behavior analytics to proactively identify issues
Implement predictive performance monitoring and capacity planning using data-driven insights
Establish SLIs, SLOs, and error budgets for mission-critical systems
Implement zero-touch provisioning and policy-driven endpoint management across Windows, Linux, and macOS environments
Deploy and manage EDR/XDR solutions with advanced threat detection and automated response capabilities
Support mobile device security and enable a secure remote workforce through strong access controls and endpoint protection