DevOps Automation Engineer #1868524

Network Designs Inc.•, VA

3d•Remote

About The Position

NDi is seeking a DevOps/CI-CD Engineer to support the FAA Chief Data Office Enterprise Information & Data Integration Program (EIDIP). The engineer will design, build, operate, and optimize the automation and technical infrastructure that supports secure, repeatable delivery of FAA applications, data services, cloud platforms, and machine-learning solutions across cloud and hybrid environments.

Requirements

U.S. Citizenship is required
Must be able to obtain and maintain a Public Trust clearance
This position is remote, candidate must reside in one of the following states: AL, AZ, DC, FL, GA, ID, MD, MS, NJ, NC, OK, OH, PA, SC, TN, TX, UT, VA, WV
Occasional travel may be required. Candidates should be able to attend meetings at FAA facilities and other locations throughout the Continental United States (CONUS) as required.
Must be available during Eastern Time (ET) business hours to support program needs and FAA coordination.
Bachelor's degree in computer science, software engineering, information technology, or a related field
Minimum 4 years of DevOps experience in an enterprise environment
Hands-on experience with GitLab, Jenkins, Ansible, Terraform, and Docker.
Knowledge of DevOps methodologies, CI/CD pipelines, automation, Infrastructure as Code, and version control using Git.
Experience with cloud services such as AWS, Azure, or Google Cloud and their DevOps capabilities.
Experience with Docker and Kubernetes for deploying and managing applications or machine-learning models.
Experience with monitoring and logging tools such as Prometheus, Grafana, and the Elasticsearch, Logstash, and Kibana stack.
Proficiency in a programming or scripting language such as Python, Java, R, or Bash.
Ability to obtain and maintain FAA Contractor Personnel Suitability.
Strong written, verbal, analytical, organizational, troubleshooting, and cross-functional collaboration skills.

Nice To Haves

FAA or other federal experience and experience working in regulated enterprise environments.
Hands-on experience deploying and managing machine-learning models and familiarity with TensorFlow, PyTorch, or scikit-learn.
Relevant cloud certification, such as AWS Certified Solutions Architect or Google Cloud Professional Data Engineer.
Relevant DevOps certification, such as Certified Kubernetes Administrator or Docker Certified Associate.
Familiarity with FAA security, governance, documentation, Agile, and continuous-delivery standards.

Responsibilities

Design, build, operate, and optimize continuous integration and continuous delivery pipelines for enterprise applications, infrastructure, data services, and machine-learning workloads.
Automate builds, tests, security scans, artifact management, deployments, environment promotion, rollback, and release controls.
Develop and maintain infrastructure-as-code and configuration automation using approved enterprise toolchains.
Support GitOps practices and reproducible infrastructure across development, test, stage, and production environments.
Manage containerized deployment patterns and orchestration for applications and machine-learning models.
Embed security, quality, compliance, monitoring, and logging controls throughout the delivery lifecycle.
Troubleshoot pipeline, deployment, infrastructure, and environment failures and lead root-cause analysis and corrective action.
Document pipelines, toolchains, operating procedures, architecture, release processes, metrics, and technical decisions.
Collaborate with software, platform, cloud, data, security, QA, and machine-learning teams to improve delivery reliability and operational performance.