Senior AI Cloud Engineer (AWS Bedrock & Generative AI)

Identify and implement the correct AWS services for alerting (e.g., CloudWatch, SNS, or Lambda) based on log anomalies.\nIntegration & Middleware: Manage and analyze Mulesoft logs to ensure seamless connectivity between legacy systems and modern AI services.\nFinancial Operations (FinOps): Monitor billing metrics for LLM usage and AWS Bedrock services to prevent cost overruns and optimize token consumption.\nPython Automation: Write production-grade Python scripts for data processing, agent logic, and infrastructure automation.\n\nTechnical Requirements (The \"Must-Haves\")\nCore AWS AI Services: Hands-on experience with AWS Bedrock and AWS Agent Core logic.\nProgramming: High proficiency in Python (specifically for data manipulation and API integrations).\nLogging & Monitoring: Deep understanding of log aggregation. Experience with Mulesoft logs is a significant plus.\nAlerting Frameworks: Ability to determine which AWS service to use for specific alerts (CloudWatch Alarms vs. EventBridge vs.

Managed Grafana).\nLLM Knowledge: Understanding of how LLMs work, including tokenization, prompt engineering, and the cost structure of different models.