Cloud DevOps Engineer (TS/SCI with Polygraph REQUIRED)

The Cloud DevOps Engineer will architect, build, manage, maintain, and monitor a robust cloud environment featuring Kubernetes clusters for hosting a variety of software development and data processing workloads. The ideal candidate is a hands-on DevOps engineer with significant experience in developing and deploying capabilities to the cloud. They must have strong, firsthand technical expertise in a variety of configuration automation, deployment, and continuous integration technologies and the proven ability to fashion robust solutions that can keep pace with mission. They must be at ease working in an agile environment with a cross-functional team. This person should embody a passion for continuous improvement and innovation. In this role, the candidate will deliver containerized applications and services, enhance CI/CD pipelines, orchestrate and monitor workloads, and troubleshoot across Dev, Test, and Prod environments.

Bachelor's degree in Computer Science, Information Technology, or other related technical discipline, or equivalent combination of education, technical certifications, training, and work/military experience.

At least five (5) years of related Kubernetes experience.

Demonstrated experience with cloud platforms like AWS, GCP, or Azure and their associated services.

Demonstrated experience with container tools, including Docker, Kubernetes, or Rancher.

Design, develop, and maintain infrastructure using IaC tools (e.g., Terraform, Ansible).

Proficiency in scripting languages including Python, Bash, and configuration formats like JSON and YAML.

Demonstrated experience with deploying Kubernetes within an on-prem or cloud-based environment.

Proficiency in utilizing Helm or other automated Kubernetes deployment methods.

Sound knowledge of Linux OS and demonstrated hands-on experience with Linux-based systems and shell scripting.

Understanding of PKI, TLS, and X.509 Authentication.

Demonstrated experience with infrastructure-as-code environments, large-scale software deployments, and/or monitoring and testing, such as continuous integration and continuous delivery (CI/CD).

Knowledge of monitoring and logging tools like Prometheus, ElasticSearch, Logstash, and Kibana.

Understanding of GitOps principles and tools like Flux and ArgoCD.

Experience in managing and troubleshooting GPU-based workloads including CUDA.

Familiarity with popular Machine Learning Frameworks like TensorFlow, PyTorch, and ONNX.

Demonstrated hands-on experience in programming and software development using Python.

Familiarity with authentication protocols such as OAuth and Keycloak.

Knowledge of container security technologies, such as Claire, Anchore, Rapid7, and/or NeuVector.

Knowledge of container registry technologies, such as Harbor, ECR, DockerHub, etc.

Work with a team to build, automate, and deploy Kubernetes workloads like containerized AI/ML solutions, data processing tools, and software applications to support mission critical applications.

Stand up and/or work with the necessary tooling for a robust CI/CD pipeline, to include: Helm, Kubernetes, Harbor, Nexus, and Terraform/Ansible.

Collaborate cross-functionally with systems engineers, software engineers, data scientists, analyst, project managers and other engineering groups.

Assist developers, DevOps engineers, and system administrators with understanding of Kubernetes architectures to take advantage of the platform environment for future capabilities.

Troubleshoot complex problems and provide customer support for software systems and application issues.

Write and update technical documentation such as system documentation, training materials, processes and procedures.

Provide recommendations for continuous improvement.

Work alongside other engineers on the team to sustain and advance our organization's capabilities.