- Set the AWS reference architecture for AI and ML systems that ingest, enrich, and exploit open-source and publicly available information at scale.
- Architect around the service gaps and parity differences between commercial AWS and the government and classified regions.
- Build the AI stack on Amazon Bedrock and Amazon SageMaker, including model access, Bedrock Guardrails, Knowledge Bases, and managed endpoints.
- Design retrieval pipelines using Amazon OpenSearch and S3 data lakes for governed, least-privilege access.
- Orchestrate workflows with AWS Step Functions and AWS Lambda, and define CI/CD with infrastructure as code using AWS CDK and Terraform.
- Extend services and capabilities to the edge for disconnected and DDIL operations and local model serving.
- Define the deployment pattern for fully air-gapped enclaves, including mirrored registries, signed model imports, and local vector stores.
- Own model governance for air-gapped and classified environments, including provenance, integrity verification, and update processes.
- Partner with security and accreditation authorities to drive ATO and continuous ATO.
AWSTerraform