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.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

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