DevSecOps Engineer

Integral•, DC

About The Position

The DevSecOps Engineer serves as the lead technical engineer responsible for the automation, continuous integration/continuous deployment (CI/CD), and security posture of the cloud infrastructure for the Office of Naval Research (ONR) Comptroller’s Office Data and Analytics (D&A) Division architecture.

Requirements

Bachelor’s Degree in computer science or IT related degree with 7 years experience
Seven (7) years of Dev/Sec/Ops or MLOps development experience combined.
Five (5) years of hands-on experience building, securing, and maintaining cloud environments (preferably AWS GovCloud or Azure Government).
Verifiable project experience on at least two projects establishing and managing Continuous Integration/Continuous Deployment (CI/CD) pipelines using tools such as Jenkins, GitLab CI, or similar.
Demonstrated expertise in implementing and managing containerization tools (e.g., Docker, Kubernetes) and Infrastructure-as-Code (e.g., Terraform, Ansible).
Hands-on experience with cloud-native security tools, including the configuration and management of Web Application Firewalls (WAF), Intrusion Detection/Prevention Systems (IDS/IPS), and Security Information and Event Management (SIEM) solutions.
Verifiable experience analyzing and parsing security data from SIEMs, audit logs, and other security data sources to identify and mitigate threats.
Secret Clearance

Responsibilities

Provide comprehensive technical infrastructure support for all systems supporting the data and analytics environment.
Design, deploy, and operate all data and applications within a cloud environment authorized at the FedRAMP High baseline and DoD Impact Level 5 (IL5), and maintain the system’s Authority to Operate (ATO) at all times lo include configuration management, security patching, system monitoring, and help desk support.
Design the architecture for scalability to accommodate future growth in data volume and user load.
Implement and sustain secure data access mechanisms, including Application Programming Interfaces (APIs) and user interfaces for data exploration, as well as a secure Bulk Data Download capability for authorized users.
Manage all access mechanisms under a formal data governance framework, including metadata management and data cataloging.
Develop and deploy machine learning (ML) and artificial intelligence (AI) models, including Natural Language Processing (NLP) to analyze unstructured text and the integration of AI/ML platforms (e.g., AWS SageMaker, Azure Machine Learning).
Automate infrastructure and workflows using Infrastructure as Code (IaC) tools (e.g., Terraform, Ansible), build and manage CI/CD pipelines for secure software deployment, and develop streaming data pipelines (e.g., using Apache Kafka or AWS Kinesis) for real-time data processing.