DevSecOps Engineer for Artificial Intelligence and Machine Learning (AI/ML)

Devsecops EngineerThe Engineer is an active participant in SAFe and Scrum development teams and meetings. Meaningful work and personal impact include automating and optimizing service deployments, integrating with enterprise authentication services, establishing and improving system monitoring while maintaining established security protocols within development, test, and production systems. Architect, build, and maintain on-premise and/or cloud infrastructure to support team and customer initiatives. Maintain and improve existing infrastructure, administer production, staging, and development environments, manage and aggregate server logs, monitor for security and system related incidents, and maintain and improve existing build and deployment processes using CI/CD tools. Enforce best practices for security and reliability, and drive security initiatives, like access control and vulnerability testing. Work with A&A teams to maintain security requirements for operation of systems, maintain up to date documentation of designs/configurations, ensure team members have continuity of recurring tasks, maintain status of operations at all times, perform after actions reporting on all outages, work with engineering teams to determine solution and root cause analysis, present findings to management for prioritization and tasking, create and determine required metrics for dashboards and service health, follow up on engineering tasks for operational solutions, validate completion, manage operational readiness board, present at weekly meetings, determine if development services are ready for automation based on best practices and maintainability, track and ensure routine operations maintenance tasks are completed in a timely manner, and aligns to the customer's strategies utilizing the customer's enterprise DevSecOps pipeline.What you'll need to succeed: Bring your cyber expertise and drive for innovation to GDIT. The DevSecOps Engineer Principal must have a bachelor of arts/bachelor of science, 8+ years of related experience, 3+ years of related systems programming experience, understanding of GitLab, Jenkins, ArgoCD, and other DevOps/Continuous Integration tools for Kubernetes, understanding of microservice design and architectural pattern best practices, understanding of Python, Bash, and Shell scripting, experience maintaining an operational environment and use of monitoring tools and dashboard interfaces (ie. Kibana, Grafana, Nagios), experience working with container images and platforms (Kubernetes/Docker/OpenShift), experience in building processes for deploying to a Kubernetes based environment using Gitlab and Helm, experience using Jira and Confluence on a daily basis, experience with deploying to on prem/data center infrastructure, strong problem solving and troubleshooting skills, strong communication and interpersonal skills, strong understanding of DevOps and software/application development processes, knowledge of network technologies, common infrastructure components, load balancers, firewalls, virtual and physical infrastructure design, must possess excellent time management skills and the drive to work unsupervised, understanding of access management and security groups (i.e. IAM, S3 bucket, SSH, VPN, etc.), and ability to write and use unit and functional testing.