Cloud Infrastructure & AI Operations Engineer (On-Site Only)

About the Opportunity

We are building the cloud and data backbone for a manufacturing floor that is becoming genuinely intelligent — AI-driven scheduling, computer-vision inspection, digital work orders, and a unified data layer running in AWS GovCloud. This role builds and runs that infrastructure. 

This is a hands-on engineering role, not a systems administration role. You will make architecture and / or tooling decisions, write infrastructure as code, build pipelines, instrument systems so they explain themselves, and work directly alongside our AI and Automation engineers to get models and services into production inside a regulated environment. 

We are deliberately open on years of experience, with one exception: you need to have worked in AWS. Everything we are building runs there, and we are not in a position to teach the platform from scratch. Beyond that, we would rather hire a sharp engineer with strong fundamentals, real automation instincts, and obvious momentum than someone with a longer resume and less curiosity. If you have provisioned AWS with Terraform, shipped through CI/CD, containerized an application, and wired up an AI-powered tool because you wanted to see if it would work — you are the profile we are looking for. Defense and compliance experience is something we will teach you. 

What You'll Do

Infrastructure as code and automation 

• Build and maintain infrastructure as code using Terraform (or CloudFormation/CDK) so environments are repeatable, reviewable, and version-controlled 
• Write automation in Python, Bash, or PowerShell to remove manual steps and speed up recurring work 
• Build and maintain CI/CD pipelines for infrastructure and application deployment using  GitLab CI. 
• Apply configuration management at scale using Ansible, AWS Systems Manager, or similar tooling 

Cloud environments and containerized workloads 

• Design, deploy, and operate secure cloud environments across AWS GovCloud and Microsoft 365 GCC High, supporting containerized applications and serverless architectures 
• Package and run containerized services using Docker, growing into orchestration on ECS or EKS 
• Build with managed and serverless services — Lambda, S3, API Gateway, Step Functions — rather than standing up servers by default 
• Partner with our AI engineers to deploy and operate AI/ML and LLM-backed workloads, including inference endpoints, data pipelines, and retrieval systems 

Observability, reliability, and cloud cost 

• Deploy centralized logging, distributed tracing, and real-time monitoring across hybrid cloud and on-premise environments using CloudWatch, or similar platforms 
• Automate monitoring configuration and alerting as code so observability ships with the infrastructure rather than after it 
• Track and alert on cloud cost and usage changes, and surface optimization opportunities to engineering leadership 
• Use AI-assisted anomaly detection and log analysis to find problems before they reach the floor, and grow into defining SLIs, SLOs, and error budgets for critical systems 

Security and compliance in a regulated environment 

• Support continuous compliance with CMMC, NIST SP 800-171, ITAR, and DFARS requirements as we prepare for third-party assessment 
• Implement identity and access management, single sign-on, least-privilege policy, and encryption in transit and at rest 
• Document systems, configurations, and control evidence to a standard that holds up under audit 
• Contribute to endpoint management and EDR/XDR operations across Windows, Linux, and macOS 

What You'll Bring

• AWS experience. Demonstrable, hands-on experience building and operating on AWS — not classroom or certification-only exposure. You should be able to walk us through services you have personally deployed and what went wrong the first time. We expect working familiarity with the core set: IAM, S3, EC2, VPC and networking, CloudWatch, and Lambda, plus at least one managed service you have used in anger 
• AWS through infrastructure as code. You have provisioned AWS resources through code rather than the console — Terraform preferred, CloudFormation or CDK accepted 
• Certification. AWS certification at any level — Cloud Practitioner, any Associate, or higher. If your hands-on depth outruns your credentials, say so in your application; we will consider it, and you would be expected to certify within your first 90 days 

Core Competencies

• Infrastructure as code. Hands-on experience writing infrastructure as code, ideally Terraform 
• CI/CD. You have built or meaningfully contributed to a deployment pipeline in Azure DevOps, GitLab, Jenkins, GitHub Actions, or similar 
• Scripting and development. Practical proficiency in Python and Bash. 
• Containers. You have built and run containerized applications with Docker or Podman 
• Observability. Experience with a monitoring or observability platform such as Datadog, CloudWatch, Grafana, or Splunk 
• Applied AI. You have built something real with modern AI tooling — an LLM-backed application, a RAG pipeline, a chatbot, or an ML workflow. Personal and academic projects count 
• Communication. You write documentation people can actually follow, and you can explain a technical decision to someone in operations or quality 

Preferred Qualifications

• Advanced AWS certification — Solutions Architect Professional, DevOps Engineer Professional, or Security Specialty 
• Any exposure to AWS GovCloud, or to AWS under a compliance regime or exposure to a regulated or compliance-driven environment — CMMC, FedRAMP, ITAR, SOC 2, HIPAA, or similar 
• Container orchestration on ECS, EKS, or Kubernetes 
• Experience with cloud cost management or FinOps practices 
• Familiarity with AI/ML platforms such as SageMaker, MLflow, Bedrock, or Kubeflow 
• Front-end or full-stack ability (React, Next.js, TypeScript) for building internal tools and dashboards 
• Exposure to manufacturing systems, SCADA, MES, industrial IoT, or edge computing 
• Certifications such as Terraform Associate, CKA, Security+, or CISSP 

What Makes This Role Different

This is not about maintaining legacy systems. You'll be:

• Building AI-first infrastructure from a clean sheet rather than inheriting a decade of technical debt 
• Working with AWS GovCloud in a secure, mission-critical environment 
• Automating everything, from deployment through incident response 
• Seeing your work land on a physical factory floor within weeks, not quarters 
• Collaborating across AI, manufacturing, and defense technology teams 
• Operating at the intersection of cloud, AI, and national security 

If you're ready to move beyond traditional sysadmin work and build the intelligent infrastructure of tomorrow, we want to hear from you.

Job Type:

• Full-Time/Permanent
• On Site Only - No Relocation Assistance at this time