Overview:
We are looking for an experienced AI/ML engineer or AWS cost optimization expert to build a Proof of Concept (PoC) system that leverages AI to analyze and optimize AWS billing data. If successful, this PoC will evolve into a long-term project with advanced forecasting, automation, and integration features.
✅ What We Need in the PoC:
The goal is to demonstrate feasibility and accuracy. The following will be evaluated:
Ingest real AWS billing data (via Cost Explorer API or CUR reports)
Detect cost anomalies (e.g., spikes, unexpected changes)
Identify underutilized resources (EC2, RDS, S3, etc.)
Provide actionable cost-saving recommendations
Display results in a simple dashboard or report
⚙️ PoC Technology Stack (Preferred):
AWS Services: Cost Explorer, CUR (S3), Lambda, Athena, QuickSight or custom dashboard
ML Tools: Python, scikit-learn, Prophet, XGBoost, or AWS SageMaker
Optional: Streamlit/Gradio for UI, or Jupyter Notebooks for explanation
💓 Success Criteria for PoC:
Connects securely to a dummy or provided AWS billing account
Highlights at least:
2+ cost anomalies
2+ underutilized resources
2+ optimization recommendations (e.g., instance right-sizing, RDS auto-pause)
Clean, interpretable, and actionable output (UI, report, or notebook)
Must provide Demo project within 50 ~ 100 USD
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