Collaborate with Product and Engineering to define, implement, and document tracking requirements for agent actions, state transitions, and user-agent interactions.
Develop and maintain monitoring systems, dashboards, and alerts for agentic interaction data correctness.
Investigate anomalies in agent event logs, trace data discrepancies, and drive timely resolutions.
Partner with AI Research and Data Science teams to align tracking with evaluation metrics.
Validate interaction data for user behavior analysis and feature assessment.
Create and maintain documentation for agent tracking specifications and QA frameworks.
Identify and implement process improvements for agent data collection pipelines.
Nice to haves:
Experience with Python for data analysis and log parsing.
Background in data pipelines, ETL processes, or real-time event streaming.
Prior experience working closely with AI or ML teams for data validation.
What you'll be doing:
Analyze agent behavior, measure the impact of new agentic features, and develop evaluation pipelines.
Collaborate with various teams to ensure tracking accuracy and data quality.
Validate interaction data for user behavior analysis and agent success metrics.
Perks and benefits:
Hybrid working model with face-to-face collaboration in Berlin campus
27 days holiday with additional days based on service years
Development opportunities with educational budget and access to courses
Health perks like gym subsidy, meditation, and health checkups
Financial benefits including Employee Share Purchase Plan and insurance
Dining perks with meal vouchers and corporate discounts