AI Infrastructure Engineer - CLEARED

Accountabilities:

• • Design and implement secure AWS infrastructure for AI/ML workloads and application modernization initiatives.

  • Develop reusable, version-controlled Terraform modules for IAM roles, VPC endpoints, Amazon Bedrock Knowledge Bases, Guardrails, and other cloud resources.

  • Manage and distribute reusable infrastructure artifacts, including Terraform modules, container images, and Lambda packages, through Artifactory.

  • Build and deploy connector infrastructure, including MCP servers and AWS Lambda-based integrations, connecting Amazon Bedrock with internal APIs, databases, ticketing systems, and other data sources.

  • Host, version, operate, and maintain connector services as production infrastructure alongside other application services.

  • Deploy custom and fine-tuned machine learning models using Amazon Bedrock Custom Model Import and Provisioned Throughput.

  • Evaluate Provisioned Throughput options, model deployment requirements, and associated cost and commitment considerations.

  • Develop cost and usage observability capabilities to track AI spending by model and developer and implement budget alerts to control cloud expenditure.

  • Establish repeatable infrastructure and deployment processes that promote consistency across development, test, and production environments.

  • Support secure cloud modernization initiatives for applications involved in federal background investigation operations.

  • Apply infrastructure-as-code, version control, automation, and repeatable deployment practices throughout the development lifecycle.

  Requirements:

  • U.S. citizenship is required.

  • An active Secret clearance and Security+ certification are required.

  • Hands-on experience with Terraform and AWS Bedrock resources, including IAM, Knowledge Bases, Guardrails, VPC endpoints, and Provisioned Throughput.

  • Demonstrated ability to develop reusable, version-controlled Terraform modules rather than relying on manual cloud configuration.

  • Experience managing and distributing versioned infrastructure artifacts through Artifactory to support reproducible deployments across development, test, and production environments.

  • Hands-on experience deploying custom and fine-tuned models using Amazon Bedrock Custom Model Import, including familiarity with open-source model weights and model size and format requirements.

  • Experience with Amazon Bedrock Provisioned Throughput and related cost, capacity, and commitment planning.

  • Experience building and operating cloud-based connector and integration services using technologies such as AWS Lambda, ECS, and containers.

  • Experience exposing internal APIs, databases, or other enterprise data sources to Amazon Bedrock agents through secure integration services.

  • Strong experience developing and maintaining cloud infrastructure and services through code, version control, and repeatable deployment processes.

  • Preferred: experience with Reinforcement Fine-Tuning (RFT) workflows on Amazon Bedrock.

  • Preferred: experience with Application Inference Profiles for per-team cost attribution.

  • Preferred: experience working within multi-account AWS Organizations environments with separate development, test, and production accounts.

  • Preferred: experience integrating Terraform and Artifactory promotion workflows into CI/CD pipelines.

  • Preferred: cross-cloud Infrastructure as Code experience with Azure and/or GCP.

  Benefits:

  • W2 hourly compensation of $70–$85 per hour, depending on experience, qualifications, location, and certifications.

  • Fully remote work opportunity within the United States.

  • Potential eligibility for paid time off (PTO).

  • Potential medical, dental, and vision coverage.

  • Potential life insurance coverage.

  • Potential long-term disability insurance.

  • Potential 401(k) plan.

  • Additional optional benefits may be available depending on compensation type and eligibility.

  • Opportunity to contribute to multi-year projects involving secure cloud modernization and emerging AI technologies.

  • Professional support and opportunities to develop skills across cloud infrastructure, AI/ML, and federal technology environments.

  • Work environment emphasizing integrity, professionalism, collaboration, and work-life balance.