{
  "name": "Production AI Observability Monitor",
  "problem": "Production AI teams need trace-level signals for latency, token growth, tool failures, and low-quality outputs.",
  "domain": "ai-observability",
  "architecture": "classifier",
  "hugging_face_tasks": [
    "text-classification",
    "token-classification",
    "summarization",
    "zero-shot-classification"
  ],
  "recommended_stack": [
    "OpenTelemetry GenAI semantic conventions",
    "OpenTelemetry Collector for vendor-neutral ingestion",
    "ClickHouse or PostgreSQL for trace analytics",
    "Prometheus and Grafana for service-level metrics",
    "MLflow for model and prompt version linkage",
    "FastAPI for trace search and regression APIs"
  ],
  "real_world_data_sources": [
    {
      "name": "Prometheus HTTP API",
      "url": "https://prometheus.demo.do.prometheus.io/api/v1/query?query=up",
      "purpose": "Real time-series telemetry for anomaly pipelines"
    },
    {
      "name": "GitHub Events API",
      "url": "https://api.github.com/events?per_page=10",
      "purpose": "Deployment-correlated public event metadata"
    }
  ],
  "job_description_skills": [
    "LLMOps observability and trace instrumentation",
    "Prompt, model, dataset, and deployment lineage",
    "SLOs, anomaly detection, and incident diagnostics",
    "High-volume telemetry storage and aggregation",
    "Evaluation-driven production monitoring"
  ],
  "impact_targets": [
    "Ingest 1,000 synthetic traces/second without loss",
    "Detect seeded latency and quality regressions with >= 0.90 precision",
    "Link 100% of traces to model, prompt, and dataset versions",
    "Generate a release health report in under 60 seconds"
  ],
  "baseline_evaluation": {
    "test_examples": 4,
    "accuracy": 1,
    "synthetic_evaluation": true
  },
  "estimated_delivery": "8-12 weeks for one engineer",
  "generated_baseline_is_production_ready": false
}