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Job Overview

Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Key points

  1. Design & Architect Data Infrastructure — Design and oversee deployment of data architecture and pipelines to capture, manage…

  2. Build & Automate Data Transformation — Develop technical tools using ML and data-engineering techniques to cleanse, organize, and transform data…

  3. Define Agentic Evaluation Metrics & Ground Truth — Partner with product and AI teams to define evaluation metrics for agentic workflows (task completeness…

  4. Build Agentic Evaluation Pipelines — Design and implement automated evaluation infrastructure that measures AI agent performance using Now LLM Service models and execution logs…

  5. Proven track record deploying, monitoring, and maintaining large-scale data systems in production; experience troubleshooting data quality issues, latency, and system reliability.

  6. Ability to design scalable, secure data architectures; experience with cloud platforms (GCP, AWS), APIs, event-driven systems, and data governance patterns.

  7. Familiarity with AI/ML evaluation frameworks, LLM-based systems, or agentic workflows; ability to instrument and evaluate complex AI systems; understanding of model performance tracking.

  8. Comfortable driving technical conversations across multiple teams; takes end-to-end ownership; works autonomously; mentors peers on data engineering standards and best practices.

Skills

Machine LearningLLMsETLPythonJavaScriptSQLAWSGoogle Cloud

Experience: Senior-level · 9+ years · Job type: Full-time

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