Location: Chantilly, VA
Security Clearance: Active TS or higher [Required] w/ CI Polygraph
Job Type: Full-Time
Target Salary Range*: $115,000 - $176,000

*This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Position Overview

The Cloud Engineer (Senior) supports advanced AI/ML workloads by designing secure, scalable cloud environments across multi-enclave and high-security settings. This role builds and optimizes cloud infrastructure for distributed model training, high-performance computing, and low-latency inference while improving automation, standardizing engineering practices, and strengthening secure cloud operations.

The Cloud Engineer (Senior) also supports hybrid and on-premises infrastructure integration, container orchestration, cross-domain connectivity, identity and access management, monitoring, data services, and DevSecOps capabilities across complex enterprise environments.

Key Responsibilities

Cloud Architecture and Integration

• Design and implement cloud architectures optimized for AI/ML compute, storage, and networking requirements.
• Integrate public cloud platforms with on-premises hyperconverged infrastructure and accelerator hardware.
• Support air-gapped hybrid-cloud and on-premises operational environments, including complex multi-enclave ecosystems.
• Support AWS GovCloud, SC2S, C2S, and GCP cloud platforms.
• Support Nutanix host and cluster environments, including Prism Central and NDFS.
• Support locally hosted GPU servers and AI-optimized infrastructure.
• Apply cloud cost-optimization techniques across supported environments.

Infrastructure Automation and DevSecOps

• Automate cloud infrastructure using DevSecOps practices and Infrastructure as Code.
• Develop and maintain Infrastructure as Code using Terraform and Ansible.
• Support Infrastructure as Code capabilities using technologies such as Bicep and CloudFormation.
• Enhance automation practices and standardize infrastructure processes across teams.
• Support advanced GitLab CI/CD pipelines and DevSecOps practices.

Secure Operations and Container Orchestration

• Support secure and highly available operations for classified or mission-critical AI applications.
• Manage containerization and orchestration platforms including Docker, Kubernetes, and OpenShift.
• Support efficient multi-tenant cloud and container environments.
• Implement cloud-native security controls and support security accreditation processes.
• Strengthen secure cloud operations across complex multi-enclave environments.

Networking and Cross-Domain Infrastructure

• Support Cisco switching, routing, firewalling, and site-to-site connectivity, including IPsec, DMVPN, and SD-WAN.
• Configure and support cloud networking and VPC environments.
• Support multi-tenant Cross-Domain Solutions.
• Support high-assurance cross-domain and encryption solutions including TACLANE and NCAP.

Identity, Security, and Governance

• Support identity and access services including Microsoft Active Directory, LDAP/OpenLDAP, Entra ID, and Keycloak.
• Implement data and model governance practices supporting secure AI pipelines.
• Apply secure cloud practices across classified, multi-enclave, and mission-critical environments.

Data Services, Monitoring, and Platform Support

• Support enterprise database services including RDS, RDS Aurora, and DynamoDB.
• Support monitoring, logging, and data platforms including Elasticsearch, OpenSearch, and Splunk.
• Support Linux operating systems including Rocky Linux, Red Hat, Amazon Linux, and Ubuntu, as well as Windows and macOS.
• Support serverless architectures using AWS Lambda.
• Support microservices architectures and API Gateway implementations.
• Apply development experience with Python, .NET/C#, and related languages to infrastructure automation and platform integration.

Qualifications

Education

• Bachelor’s degree. [Required]

Experience

• Minimum 8 years of relevant experience. [Required]
• Hands-on experience with major cloud providers including AWS, Azure, and GCP. [Required]
• Experience with Kubernetes and cloud networking and storage optimization. [Required]

Skills

• Knowledge of cloud engineering, infrastructure, or related technical disciplines. [Required]
• Knowledge of AI/ML compute environments, distributed systems, or high-performance computing. [Required]
• Experience with Infrastructure as Code tools including Terraform, Bicep, and CloudFormation, and with DevSecOps pipelines. [Required]
• Strong understanding of secure cloud practices and multi-enclave operations. [Required]
• Effective communication and cross-team collaboration skills. [Required]

Preferred Qualifications

• Experience with hybrid or multi-cloud integrations.
• Familiarity with GPU and accelerator hardware and AI-optimized cloud patterns.
• Cloud certifications such as AWS Solutions Architect or Azure Architect.
• Experience working in high-security or classified environments.