DevSecOps & Platform Engineering: Design, build, and maintain secure, scalable platform capabilities supporting application development and delivery within AWS GovCloud. Develop reusable infrastructure, automation, deployment patterns, and platform services that improve engineering consistency, security, and developer productivity.
AWS GovCloud Architecture & Management: Design, implement, and maintain secure, scalable, and compliant AWS GovCloud environments supporting DoD and federal applications. Work with AWS services including Amazon EKS, ECS/Fargate, IAM, VPC, S3, CloudWatch, and other approved cloud-native services.
DevSecOps Pipeline Development: Build, maintain, and improve CI/CD pipelines using technologies such as GitLab CI/CD, Jenkins, AWS CodePipeline, and related tooling. Automate application and infrastructure deployments while integrating testing, security scanning, compliance checks, and deployment controls into delivery workflows.
Infrastructure as Code (IaC): Automate infrastructure provisioning and configuration using technologies such as Terraform, CloudFormation, and Ansible. Develop reusable infrastructure components and apply version control, peer review, automated validation, and repeatable deployment practices.
Containerization & Orchestration: Deploy and operate containerized applications using Docker/OCI containers and Kubernetes, including Amazon EKS. Support workload configuration, networking, storage, secrets, scaling, resource management, upgrades, security, and troubleshooting.
Security & Compliance: Integrate security throughout the software development lifecycle and support compliance with applicable federal cybersecurity frameworks, including NIST 800-53, NIST 800-171, RMF, FedRAMP, STIGs, and Zero Trust principles. Implement and support automated security capabilities including SAST/DAST, software composition analysis, container scanning, IaC scanning, secrets detection, vulnerability management, and compliance validation.
AI Platform Enablement: Support the cloud infrastructure and shared platform capabilities required to securely deploy and operate AI-enabled applications and services. Work with AI and software engineering teams to establish repeatable patterns for deployment, configuration, access control, security, monitoring, scalability, and operational support.
AI/LLM Service Integration: Support the secure integration and operation of approved AI and LLM services, including platforms such as Amazon Bedrock and other enterprise AI services. Assist engineering teams with infrastructure, authentication and authorization, API connectivity, configuration, deployment automation, monitoring, and operational troubleshooting.
Monitoring, Observability & Incident Response: Implement monitoring, logging, tracing, dashboards, and alerting across cloud infrastructure, Kubernetes, applications, and platform services using technologies such as AWS CloudWatch, Security Hub, GuardDuty, Splunk/ELK, Prometheus, Grafana, OpenTelemetry, or comparable solutions. Participate in incident response, root-cause analysis, vulnerability remediation, and continuous reliability improvements.
Automation & Scripting: Develop automation and platform tooling using Python, Bash, PowerShell, or similar technologies to eliminate repetitive operational tasks, integrate services and APIs, enforce platform standards, and improve deployment efficiency.
Production Operations: Troubleshoot complex infrastructure, application, CI/CD, Kubernetes, networking, and cloud service issues in production and production-like environments. Support operational readiness, system reliability, capacity, performance, and continuous improvement.
Collaboration & Knowledge Sharing: Work closely with software engineers, AI engineers, cybersecurity teams, cloud engineers, architects, and mission stakeholders to integrate security, automation, and platform capabilities throughout the software development lifecycle. Develop technical documentation, architecture diagrams, runbooks, and reusable engineering standards.