Cloud DevOps Engineer
JOB DESCRIPTION
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.
QUALIFICATIONS
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
REQUIRED QUALIFICATIONS
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)
DESIRED QUALIFICATIONS
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.
KEY RESPONSIBILITIES
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