This role pays more than
92%
of similar roles. Most pay
$213,939–$287,300
— the shaded band above.
At the midpoint, this role pays about
$324k
versus about
$251k
for comparable roles.
Based on 240 similar postings.
Employer
About Adobe
Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software
Adobe currently has
277 open roles
on FindRole.
Listed pay typically runs
$148,100–$265,350
across 111 roles with salary data.
The Sr. Director, AI, Data Science & Engineering will lead the technical organization responsible for building next-generation AI-powered fraud, abuse, Trust & Safety, and consumer protection capabilities. This leader oversees AI Engineering, Data Science and Machine Learning, and Data Engineering teams to move complex risk problems from concept to production. Key responsibilities include defining technical strategies for agentic systems, graph intelligence, anomaly detection, behavioral modeling, and real-time risk decisioning. The role requires building scalable systems using generative AI, large language models, and traditional machine learning. You will partner with Platform Risk teams on identity graphs, browser fingerprinting, and bot detection. Success involves establishing engineering standards for reliability and observability while integrating telemetry and risk signals into cohesive detection systems to improve fraud prevention and operational efficiency.
Lead the AI Engineering, Data Science, and Data Engineering organizations for Consumer Trust.
Define and execute the technical strategy for AI and ML applications in fraud, abuse, and safety.
Manage the end-to-end development of AI capabilities from initial experimentation through production deployment.
Drive the development of agentic AI, graph intelligence, anomaly detection, and real-time risk decisioning.
Build scalable data, feature, evaluation, and ML infrastructure to support high-volume production systems.
Integrate platform signals, identity intelligence, and telemetry into cohesive detection and decisioning systems.
Establish engineering standards for AI reliability, observability, scalability, and responsible AI practices.
Recruit and develop multidisciplinary technical talent across AI, machine learning, and data engineering.
What we're looking for
Significant experience building and deploying AI and machine learning systems in production at scale.
Strong technical background in modern AI/ML, including generative AI, large language models, agentic systems, and model evaluation.
Demonstrated experience leading multidisciplinary organizations across AI/ML, data science, and data engineering.
Strong production engineering and systems architecture experience to take AI capabilities from prototype through production.
Experience with large-scale data platforms, telemetry, real-time systems, feature pipelines, and ML infrastructure.
Strong understanding of distributed systems and engineering requirements for high-volume, low-latency decisioning.
Experience in fraud prevention, cybersecurity, identity, platform abuse, Trust & Safety, or other adversarial environments.
Experience with identity resolution, graph ML, or real-time risk platforms (preferred); experience deploying generative AI into high-impact production (preferred).