Senior AWS AI/MLOps Solution Architect
Posted Updated
Job Description:
Lead the technical architecture and platform-enablement work required to deploy a secure, scalable, AWS-hosted AI assistant that integrates with the War Data Platform/Databricks and enterprise knowledge sources.
Lead the technical architecture and platform-enablement work required to deploy a secure, scalable, AWS-hosted AI assistant that integrates with the War Data Platform/Databricks and enterprise knowledge sources.
- 9+ years of experience designing and delivering cloud, data, AI, or MLOps platforms, including responsibility for production architecture and nonfunctional requirements.
- Demonstrated experience architecting AI/ML applications on AWS using services such as Amazon Bedrock and/or SageMaker, API Gateway, Application Load Balancer, ECS or EKS, ECR, S3, IAM, KMS, Secrets Manager, CloudWatch, and CloudTrail.
- Experience designing containerized application architectures using Docker and AWS container-orchestration services, including scalability, availability, networking, security, and operational support.
- Experience integrating external applications with Databricks through REST APIs, including the Databricks Genie Conversation API, SQL Statement Execution API, SQL Warehouses, or comparable Databricks APIs.
- Knowledge of Databricks identity and governance capabilities, including OAuth, service principals, user-level access, Unity Catalog permissions, row-level security, column masking, governed views, and audit logging.
- Ability to design secure authentication and authorization flows involving CAC/enterprise SSO, OIDC or OAuth, identity federation, and on-behalf-of-user access patterns.
- Experience defining infrastructure and platform dependencies across separately managed environments, including network connectivity, PrivateLink or private API access, DNS, certificates, firewall rules, IAM roles, security approvals, and service enablement.
- Experience designing RAG architectures that connect to Microsoft SharePoint and other enterprise repositories using AWS or Databricks vector-search capabilities.
- Ability to define target-state architecture, deployment patterns, technical requirements, implementation roadmaps, security controls, and platform-enablement requests for AWS and Databricks platform owners.
- Experience working directly with platform, cybersecurity, cloud, networking, data-governance, and application-development stakeholders to move an architecture from concept through production deployment.
- Experience working within the War Data Platform, formerly Advana, or another DoD enterprise data platform.
- Experience with Databricks Genie, Unity Catalog, Databricks Vector Search/AI Search, and SQL Warehouses.
- Experience deploying solutions in AWS GovCloud, DoD IL4/IL5, CUI, or other regulated environments.
- Experience with infrastructure as code using Terraform, AWS CloudFormation, or AWS CDK.
- Familiarity with Microsoft Graph, SharePoint ingestion, document-level access controls, and enterprise RAG security.
Skills
- AI
- API
- API Gateway
- Authentication
- AWS
- AWS Bedrock
- CDK
- Cloud
- CloudFormation
- CloudTrail
- CloudWatch
- Cybersecurity
- Data Governance
- Databricks
- DNS
- Docker
- ECS
- EKS
- Firewall
- IAM
- Infrastructure as Code
- Machine Learning
- MLOps
- Networking
- OAuth
- OpenID
- REST
- S3
- SageMaker
- SharePoint
- SQL
- SSO
- Terraform
- Unity
- Unity Catalog
- Vector Search