QUALIFICATIONS:- minimum Top Secret (TS) with eligibility to access SCI material
- 8+ years of experience
- Knowledge of cloud engineering, infrastructure, or related technical roles.
- Hands on experience with major cloud providers (AWS, Azure, GCP).
- Knowledge of AI/ML compute environments, distributed systems, or HPC.
- Skills in IaC (Terraform, Bicep, CloudFormation) and DevSecOps pipelines.
- Experience with container orchestration (Kubernetes) and cloud networking/storage optimization.
- Strong understanding of secure cloud practices and multi enclave operations.
- Effective communication and cross team collaboration skills.
Unique Skills / Technical Requirements:- Air-gapped hybrid cloud and on-premises operational environments, including complex
- multi-enclave ecosystems
- AWS GovCloud/SC2S/C2S and GCP cloud platforms Nutanix host and cluster
- configuration, management with Prism Central, and NDFS configuration/management
- Cisco switching, routing, firewalling, and site-to-site functionality (such as IPSEC,
- DMVPN, and SD-WAN)
- Locally hosted GPU servers
- Multi-tenant Cross-Domain Solutions (CDS)
- Infrastructure-as-Code (Terraform, Ansible)
- Containerization and orchestration (Docker, Kubernetes, OpenShift)
- Cloud-native security implementation and security accreditation processes
- Advanced GitLab CI/CD pipelines and DevSecOps practices
- Enterprise database services (RDS, RDS Aurora, DynamoDB)
- Serverless architectures (Lambda)
- Cloud networking and VPC configuration
- Monitoring, logging, and data platforms (Elasticsearch, OpenSearch, Splunk)
- Microservices architecture and API Gateway implementation
- Development experience with Python, .NET/C#, and related languages
- Identity and access services (Microsoft Active Directory, LDAP / OpenLDAP, Entra ID,
- Keycloak)
- High-assurance cross-domain and encryption solutions (TACLANE, NCAP)
- Cloud cost-optimization techniques
- Operating Systems: Linux (e.g., Rocky, RedHat, Amazon, Ubuntu), Windows, and Mac
- OS
Preferred Qualifications:- Experience with hybrid or multi cloud integrations.
- Familiarity with GPU/accelerator hardware and AI optimized cloud patterns.
- Cloud certifications (e.g., AWS Solutions Architect, Azure Architect).
- Experience working in high security or classified environments.
Preferred locations: (onsite) Chantilly, VA or Washington DC Capital Region facility
Certain states and localities require employers to post a reasonable estimate of salary range. A reasonable estimate of the current base pay range for this position is $155,00.00 to $165,000.00 annually. Actual salary will be based on a variety of factors, including shift, location, experience, skill set, performance, licensure and certification, and business needs. The range for this position in other geographic locations may differ. Certain positions may also be eligible for variable incentive compensation, such as bonuses or commissions, that is not included in the base pay.
The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full-time employees:
- Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
- Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
- Paid Time Off: PTO and Sick Leave (starting at 20 days per year) & Holidays (10 per year), Parental Leave, Military Leave, Bereavement
- Additional Perks: Nursing Mothers Benefits, Voluntary Legal, Pet Insurance, Employee Discount Program
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This is a full-time direct hire position, and you must currently have an active TS/SCI Security Clearance or above. We are not able to offer visa sponsorship, 1099 status, or work with C2C for this role.What will you be doing?WWT is seeking a Senior Cloud Engineer (AI Integration) 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 compute, and low latency inference. The engineer enhances automation practices, standardizes processes across teams, and strengthens secure cloud operations.
RESPONSIBILITIES:- Design and implement cloud architectures optimized for AI/ML compute, storage, and networking needs.
- Automate cloud infrastructure using DevSecOps and Infrastructure as Code (IaC) tools.
- Integrate public cloud platforms with on premises hyperconverged systems and accelerator hardware.
- Support secure, high availability operations for classified or mission critical AI applications.
- Manage container orchestration platforms and ensure efficient multi tenant operations.
- Implement data and model governance practices to maintain secure AI pipelines.
Knowledge/Skill Description - Extensive experience with modern frontend frameworks, backend technologies, APIs, and relational/non-relational databases.
- Strong knowledge of software architecture, system integration, and scalable application design.
- Experience with secure development practices, DevSecOps methodologies, and CI/CD pipelines.
- Expertise in database design, performance optimization, and application troubleshooting.
- Proven ability to lead technical initiatives and establish development standards across teams.
