(265) Cloud Engineer

Company Summary

Arlo Solutions (Arlo) is an information technology consulting services company that specializes in delivering technology solutions. Our reputation reflects the high quality of the talented Arlo Solutions team and the consultants working in partnership with our customers. Our mission is to understand and meet the needs of both our customers and consultants by delivering quality, value-added solutions. Our solutions are designed and managed to not only reduce costs, but to improve business processes, accelerate response time, improve services to end-users, and give our customers a competitive edge, now and into the future. 

Position Overview

Arlo is seeking a highly skilled and motivated Cloud Engineer to support the National Oceanic and Atmospheric Administration (NOAA) National Marine Fisheries Service (NMFS) Cloud Program Office Initiative. The successful candidate will be responsible for implementing and managing cloud infrastructure, developing AI/ML capabilities, migrating workloads, and ensuring the security and operational efficiency of the cloud platform. This role involves close collaboration with NOAA stakeholders to prioritize efforts, determine necessary resources, and deliver high-value cloud services aligned with NOAA Fisheries' mission.

Job Responsibilities and/or Success Factors

• Implement and manage a centralized management platform to provide visibility and control over the cloud environment.
• Leverage Infrastructure as Code (IaC) to automate resource deployment and employ workload orchestration tools.
• Design and implement scalable cloud infrastructure to support rapid prototyping and development of AI/ML solutions
• Create cloud cost plans using CSP-provided tools (i.e., Google Cloud pricing calculator)
• Oversee cost management tools and utilization.
• Migrate, configure, and deploy virtual networks according to design specifications.
• Configure network connections, firewalls, and load balancers provided by the government.
• Utilize cloud migration tools to facilitate the transfer of applications and manage data storage, replication, and governance.
• Develop cloud-based AI capabilities and Machine Learning models.
• Integrate diverse data types (images, documents, video, audio) to support AI development.
• Utilize open-source technologies and cloud-based tools to develop and train ML models.
• Implement monitoring to maintain continuous compliance with security controls and organizational policies.
• Transition to higher-value cloud services to optimize cost and performance.
• Assist with configuration and maintenance of automated monitoring and alert tools.
• Monitor data ingestion pipelines, staging, and production environments.
• Centralize log management tools.
• Utilize agile best practices to support design, development, testing, and deployment.
• Establish and support documentation standards and version control.
• Maintain a knowledge repository inclusive of SOPs, reporting, architecture diagrams, configuration guidelines, and network settings.
• Develop AI Proof-of-Concepts by integrating and ingesting various data types.
• Transition AI/ML proof-of-concept solutions to a production environment.
• Conduct comprehensive documentation, knowledge transfers, and training.
• Assist in vulnerability management, protective monitoring, incident management, and configuration and change management.
• Implement continuous monitoring to detect and track vulnerabilities.
• Develop and implement robust data governance frameworks.
• Establish data governance processes and policies for data lifecycle management.
• Establish standards and best practices for data integration and interoperability.
• Utilize generative AI technologies to facilitate data integration across schemas and taxonomies.
• Develop a cloud rationalization framework to guide the evaluation and prioritization of cloud assets.
• Develop detailed designs for landing zones based on approved managed services.
• Deploy proof-of-concept to the configured landing zone and validate its configuration.
• Implement processes for ongoing compliance with organizational policies and security controls.
• Develop comprehensive documentation for landing zones.

Education and Minimum Qualifications

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• Proven experience in cloud engineering, AI/ML development, and cloud operations.
• Proficiency with cloud platforms such as AWS, Azure, or Google Cloud.
• Professional or Associate level cloud certification from major cloud service provider (AWS, Azure, or Google Cloud)
• Strong knowledge of Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• Experience with cloud migration tools and techniques.
• Familiarity with AI/ML frameworks and tools such as TensorFlow, PyTorch, or similar.
• Strong understanding of security controls and compliance requirements.
• Excellent problem-solving skills and ability to work collaboratively with stakeholders.
• Strong communication skills and ability to document technical processes clearly.
• Experience working with government agencies or in a regulated environment.
• Certifications in cloud platforms.
• Experience with data governance frameworks and best practices.

AAP Statement

We are proud to be an Affirmative Action and Equal Opportunity Employer and as such, we evaluate qualified candidates in full consideration without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, national origin, age, disability status, protected veteran status, and any other protected status.