Sr. Director, AI, Data Science & Engineering

What you'll do

• Set and execute AI/ML strategy and lead end-to-end development, deployment, monitoring, and operation of production systems.
• Build capabilities such as agentic AI, graph intelligence, anomaly detection, behavioral models, and real-time risk decisioning.
• Develop and lead multidisciplinary teams, partner on shared risk platforms, and establish engineering standards for reliable, responsible AI.

What they ask for

• Significant experience building and deploying AI/ML systems in production at scale.
• Strong modern AI/ML expertise, including generative AI, large language models, agentic systems, model evaluation, and traditional machine learning.
• Demonstrated leadership across AI/ML, data science, and data engineering, with production engineering and systems architecture experience.
• Experience with large-scale data platforms, telemetry, real-time systems, feature pipelines, or ML infrastructure; understanding of distributed systems and high-volume, low-latency decisioning.

Nice to have

• Experience in fraud prevention, cybersecurity, identity, platform abuse, Trust & Safety, payments risk, bot detection, or other adversarial environments.
• Experience with identity resolution, identity graphs, graph ML, browser or device intelligence, behavioral signals, reputation systems, real-time risk platforms, or production generative AI/agentic systems.

Pay

USD $211,600 - $436,975 annually (base salary); USD $281,100 - $436,975 (base salary, California)

Tools

AI/ML, generative AI, large language models, agentic systems, graph ML, feature pipelines, ML infrastructure, distributed systems

AI focus

Leads development and production deployment of AI/ML for fraud, abuse, Trust & Safety, and consumer protection, including generative and agentic AI, graph intelligence, anomaly detection, behavioral modeling, and real-time risk decisioning.