AI Engineer

Job Summary

You will develop and deploy AI/ML solutions focusing on Amazon Bedrock knowledge bases, skill marketplaces, and Microsoft Exchange integration, while supporting backend development and cloud infrastructure to enhance system observability, security, and cost management.

Responsibilities

• Design and implement document ingestion pipelines, vector indexing, and retrieval-augmented generation (RAG) tuning for Amazon Bedrock knowledge bases to optimize AI/ML model performance
• Develop and validate skill packaging and integrate AgentCore gateway with version control to enhance skills marketplace functionality
• Integrate Microsoft Exchange connector using Graph API and OAuth, managing draft-review-send workflows with human-in-the-loop patterns to improve communication processes
• Deploy AI/ML applications to ECS and AgentCore runtime environments ensuring reliable operation
• Aggregate APIs and shape responses in the backend-for-frontend (BFF) layer to streamline data delivery
• Implement authentication and session management using federated Active Directory and OAuth token exchange to secure user access
• Manage access control at agent, skill, and knowledge base levels using IAM policies, resource-level permissions, and sharing workflows to enforce security
• Monitor agent and large language model (LLM) performance using CloudWatch dashboards and Bedrock model invocation metrics to maintain system health
• Track costs and allocate billing through resource tagging and Cost Explorer reporting by user and department to optimize budget management
• Maintain audit logs for permission changes, agent/skill access, and knowledge base activity to ensure compliance and traceability
• Provision cloud infrastructure using Infrastructure as Code tools such as CloudFormation and CDK to automate environment setup
• Manage multi-environment deployments and go-live processes using CI/CD pipelines, runbooks, and scaling policies to ensure smooth releases

Preferred competencies and qualifications

• Experience in backend or application development focusing on API aggregation and authentication mechanisms
• Familiarity with DevOps practices including observability, cost tracking, audit logging, and infrastructure automation