Cloud Engineer (Senior)
About The Position
The Cloud Engineer (Senior) supports advanced AI/ML workloads by designing secure, scalable cloud environments across multi-enclave and high-security settings. The 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. It 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. The position supports AWS GovCloud, SC2S, C2S, and GCP, as well as Nutanix environments, locally hosted GPU servers, air-gapped hybrid-cloud and on-premises environments, and classified or mission-critical AI applications. The work includes cloud architecture and integration, infrastructure automation, secure operations, container orchestration, networking, identity and security, governance, data services, monitoring, and platform support.
Requirements
- Bachelor’s degree.
- Minimum 8 years of relevant experience.
- Active TS or higher security clearance with CI Polygraph.
- Hands-on experience with major cloud providers including AWS, Azure, and GCP.
- Experience with Kubernetes and cloud networking and storage optimization.
- Knowledge of cloud engineering, infrastructure, or related technical disciplines.
- Knowledge of AI/ML compute environments, distributed systems, or high-performance computing.
- Experience with Infrastructure as Code tools including Terraform, Bicep, and CloudFormation, and with DevSecOps pipelines.
- Strong understanding of secure cloud practices and multi-enclave operations.
- Effective communication and cross-team collaboration skills.
Nice To Haves
- 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.
Responsibilities
- 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.
- Automate cloud infrastructure using DevSecOps practices and Infrastructure as Code.
- Develop and maintain Infrastructure as Code using Terraform and Ansible, and support capabilities using Bicep and CloudFormation.
- Enhance automation practices and standardize infrastructure processes across teams.
- Support advanced GitLab CI/CD pipelines and DevSecOps practices.
- 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.
- 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 and high-assurance cross-domain and encryption solutions, including TACLANE and NCAP.
- 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.
- 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 and microservices architectures and API Gateway implementations.
- Apply development experience with Python, .NET/C#, and related languages to infrastructure automation and platform integration.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
