Cloud DevOps Developer - MLSpace Integration bei Red Arch Solutions
Red Arch Solutions · Reston, Vereinigte Staaten Von Amerika · Onsite
- Professional
- Optionales Büro in Reston
Overview:
Red Arch Solutions is seeking a Cloud DevOps Developer to join our dynamic team working with a federal agency in Reston, VA. The Cloud DevOps Developer will be responsible for customizing an AWS MLSpace-based analytic environment for integration with the agency's cloud-based enterprise infrastructure. The ideal candidate will have significant knowledge of AWS data-related and ML/AI services, OpenShift/Kubernetes, CI/CD pipelines and demonstrable experience in developing scalable, efficient cloud solutions. The candidate must be a proven high performer/self-starter who can rapidly acquire expert knowledge of AWS MLSpace and Zero Trust principles to apply to development tasks. Background with MLDC and AI concepts and technologies is a plus.This position offers a unique opportunity to contribute to cutting-edge technology while supporting national security efforts
.
Key Responsibilities:
Required Skills and Experience:
Desired Skills:
Red Arch Solutions is seeking a Cloud DevOps Developer to join our dynamic team working with a federal agency in Reston, VA. The Cloud DevOps Developer will be responsible for customizing an AWS MLSpace-based analytic environment for integration with the agency's cloud-based enterprise infrastructure. The ideal candidate will have significant knowledge of AWS data-related and ML/AI services, OpenShift/Kubernetes, CI/CD pipelines and demonstrable experience in developing scalable, efficient cloud solutions. The candidate must be a proven high performer/self-starter who can rapidly acquire expert knowledge of AWS MLSpace and Zero Trust principles to apply to development tasks. Background with MLDC and AI concepts and technologies is a plus.This position offers a unique opportunity to contribute to cutting-edge technology while supporting national security efforts
.
Key Responsibilities:
- Collaborate with cross-functional teams to design, develop, and maintain custom cloud-based solutions for MLSpace integration with agency-specific enterprise services and tools.
- Design, implement and utilize a robust, documented code configuration management system using Gitlab Ultimate that facilitates intelligent forks and merging requirements for customized code developed against an OpenSource baseline
- Develop and implement CI/CD pipelines and automations, infrastructure as code (IaC), and continuous monitoring solutions.
- Contribute to the design of cloud architecture that meets the agency’s performance, security, and scalability requirements, with particular consideration of Zero Trust requirements.
- Provide high-quality documentation for all work products, to include both development-related products as well as Agile scrum reporting inputs.
Required Skills and Experience:
- Active TS/SCI with Polygraph clearance.
- Master’s degree in computer science or a related field, plus three (3) years of experience in software engineering or cloud development OR a Bachelor’s degree with five (5) years of experience, OR seven (7) years of relevant experience.
- Knowledge of AWS MLSpace, AWS SageMaker and AWS Bedrock for AI and machine learning integration
- Strong experience with cloud-native development and tools, including AWS Lambda, EC2, S3, and other AWS services.
- Proficiency in Python and the ability to develop, deploy, and maintain Python-based cloud applications as well as front-end REACT web-based UI applications.
- Experience with containerization and scaled deployments using OpenShift/Kubernetes
- Familiarity with AI/ML tools and frameworks such as TensorFlow, PyTorch, or SageMaker.
- Experience in developing Infrastructure as Code (IaC) using tools like Terraform or Ansible.
- Significant experience with CI/CD pipelines and tools such as GitLab CI, Jenkins, Artifactory and automated security scanning and testing frameworks.
- Strong understanding of Linux CLI, cloud-based networking, and systems administration.
- Excellent problem-solving skills and the ability to troubleshoot cloud and infrastructure issues.
- Excellent communication skills
Desired Skills:
- Knowledge and experience with AWS MLSpace
- Experience with Gitlab Ultimate for code management, Agile Scrum-based project management and documentation.
- Experience with Splunk for data collection and monitoring.
- Knowledge of Elasticsearch and other log management solutions.
- Experience in working with Log Management tools for secure and efficient logging.
- Knowledge of Zero Trust principles
- Knowledge of and experience supporting the Machine Learning Development Cycle (MLDC)
