Arize AI
GrowthLLM observability and evaluation platform. FDEs embed with ML teams to deploy tracing, monitoring, and evaluation pipelines for models already in production. Setting up hallucination detection, latency dashboards, and automated regression testing across model updates.
Signals from job descriptions
Patterns mined from Arize AI's open FDE postings
- 01
Prompt tracing and hallucination detection are explicitly listed skills. FDEs here troubleshoot live AI systems in production, not just set them up.
- 02
OpenAI and Anthropic model evaluation appears together in role requirements, signaling Arize is positioned as model-agnostic observability infrastructure.
- 03
LLM evals as a discipline is new enough that Arize FDE roles are effectively defining the job function as the field matures.
Tech stack
Inferred from job descriptions
Languages
AI / ML
Cloud & infra
Tools & integrations
Sectors
Hiring regions
- United States
- Remote
- Asia-Pacific
Seniority mix
- Mid-level / unspecified5
Put an embedded AI team on your roadmap
Forward-deployed engineers to deploy, AI-native engineers to build, and on-demand QA pods to validate, embedded with your team, starting the same day.