Artificial Intelligence

• Lead end-to-end observability design for AI/ML features in production and internal usage (e.g., RAG, Copilots, LLM-enhanced customer experiences).
• Instrument AI features in Tealium products (e.g., ML-powered segmentation, decisioning, or predictions) for latency, accuracy, drift, usage, and cost.
• Implement monitoring and cost tracking for third-party AI services (OpenAI, Anthropic Claude, Amazon Q, etc.), including rate limiting, quota management, and failover strategies.
• Build telemetry pipelines to track LLM request/response metrics, prompt engineering observability, token usage, hallucination detection, and failover.
• Collaborate with data science and product teams to define and automate quality SLIs/SLOs for models.
• Implement AI-aware tracing (e.g., OpenTelemetry + LangChain/LLM traces) into the broader observability stack.
• Participate in on-call rotations and help triage AI-specific incidents related to model regressions, latency spikes, or API failures.
• Automate validation pipelines to ensure AI features are robust across environments.
• Establish dashboards and alerts for AI observability using tools like Datadog, Sumologic, Prometheus, OpenTelemetry, and Grafana.
• Contribute to ethical AI monitoring practices: PII exposure detection, prompt abuse, fairness, and content compliance.
• Help guide Tealium’s use of Generative AI developer tools (e.g., GitHub Copilot, Amazon Q Developer, Cursor) for coding efficiency and ensure telemetry around their use is captured appropriately.
• Initial goal within 6 months: Establish baseline AI observability across 3+ production ML features.

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