DevOps Engineer (Active Secret Clearance

StriveWorks, Inc
Schofield Barracks, HI, United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$220,000.0 - $270,000.0
Working hours
Regular working hours
Job source

Tech stack

Amazon Web Services Microsoft Azure Bash Shell Cloud Computing Continuous Integration Linux DevOps Information Security Management Python (Programming Language) Server Administration Software Deployment Spring Cloud
+7 more
Containerization Kubernetes Terraform Devsecops Golang Programming Languages Microservices

Job description

As a Senior DevOps Engineer based at Schofield Barracks, you will own what you deploy. That means maintaining, optimizing, and enhancing the environments that national security customers depend on. You’ll deploy custom K8s clusters, manage IaC automation, and serve as the operational link between platform developers and customer-facing teams. In this role, you will bring junior DevOps teammates along as you go, and you will have the latitude to explore better solutions when you find them.

Requirements

We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership-because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice., 6+ years of direct, hands-on experience in:

  • Microservices deployment in Kubernetes
  • Diagnosing and resolving issues within containerized environments
  • Helm Chart and Kustomizations development/deployment
  • Python and/or Golang programming, or other general purpose programming languages
  • Automation and IaC, e.g., Terraform
  • Cloud infrastructure: AWS and Azure
  • Managing and troubleshooting Linux systems, e.g., networking and bash scripting
  • Active Secret (or above) US security clearance and US citizenship

The following isn’t required, but we’d love to see it:

  • Experience with DOD networking, tools, infrastructure, security requirements, and policies
  • Proficiency with US federal information system security policies including STIGs, NIST SP 800-171, NIST SP 800-53, CMMC, and ICD 503
  • Experience with software deployments to unclassified, CUI, and classified DOD networks
  • Experience with DevSecOps and CI/CD for GPU-enabled server administration and deployment
  • Experience deploying or maintaining CNCF projects
  • Experience with NAS and SAN technologies
  • Experience with K8s and cloud-native applications in DDIL environments

This role is hybrid/on site at customer sites at Schofield Barracks in Oߵahu, Hawaiߵi. You will be expected to travel up to 30% of the time, including some international travel.

Benefits & conditions

The anticipated base pay range for this position is $220,000-$270,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses., * Medical/dental/vision insurance

  • Voluntary life, long-term disability, accident, and hospital indemnity insurance
  • HSA and FSA (including dependent care FSA) plans
  • 401(k) plan
  • Unlimited PTO
  • Paid parental leave

Ready to build systems that work for a mission that matters? Let’s talk.

About the company

“In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it.” - Dr. Jim Rebesco, Cofounder and CEO, Striveworks

The government’s demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.

Striveworks was built to solve that problem.

What you’ll build

Since 2018, we have delivered the most trusted AI systems operating in real-world use cases-providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.

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