OpenCTI AI Engineer for RAG and Agent pipelines

I need an experienced Python engineer who already knows their way around OpenCTI and can embed advanced, agent-based AI capabilities into the platform. The immediate focus is on predictive analytics: building modules that surface anomalies in threat-intel data, fire real-time alerts, and forecast emerging patterns so we can stay ahead of attackers.

The work will sit on AWS, so please be fluent with the usual services (Lambda, ECS/EKS, S3, DynamoDB or RDS) and comfortable wiring everything together with infrastructure-as-code. Retrieval-Augmented Generation (RAG) techniques will power part of the solution, so you should understand vector stores, embeddings, and prompt engineering well enough to fine-tune them for security data.

Core deliverables
• Python micro-services or OpenCTI connectors that perform anomaly detection and trend forecasting
• A RAG pipeline that enriches results with external intelligence sources
• Automated tests plus deployment scripts for a frictionless push to our AWS environment
• Brief technical runbook so my team can maintain and extend what you build

Acceptance criteria
1. Models detect and alert on outliers with