As a Principal AI Engineering Architect, you will be tasked with leading the development and deployment of SentinelOne's next-generation AI-powered cybersecurity solutions. This critical role will shape SentinelOne's competitive advantage by translating cutting-edge AI research into production-grade, globally scalable products that proactively stay ahead of cybercriminals and tomorrow's threats. You will drive the strategy and execution for our core AI platforms, directly impacting our ability to deliver industry-leading protection to our customers.
What Will You Do?
Define and execute the technical roadmap for AI engineering, focusing on bringing the most recent advances in machine learning technology to help our customers efficiently discover and defeat threats.
Represent AI Engineering as a key contributor to the Architecture Board defining the overall architecture strategy for the SentinelOne Platform and Services.
Understand and define strategies to support cross domain requirements to use AI Platform and Services across SentinelOne.
Serve as a lead individual contributor who also mentors across distributed teams, fostering a culture of technical excellence and continuous innovation.
Design and build net-new AI capabilities to be used across SentinelOne's industry-leading cybersecurity platform.
Drive cross-functional collaboration across multiple engineering teams to ensure seamless integration and innovation in AI-powered cybersecurity products.
Oversee the establishment of best practices for MLOps, security, and performance monitoring to ensure the reliability and efficacy of our AI defense mechanisms.
Qualifications
15 or more years of progressive experience in software or machine learning engineering.
Proven track record of delivering multiple high-scale, production-ready AI or data products from concept through deployment and maintenance.
Deep expertise in building highly available, low-latency machine learning systems, including experience with machine learning workflows and processes.
Experience in endpoint security, OS concepts, or a related field with comparable large-scale event processing and real-time processing challenges.
Demonstrated ability to mentor, develop, and retain top-tier AI engineering talent.
Expert-level knowledge of Python and modern frameworks (e.g., Pydantic), cloud-native MLOps platforms (e.g., Kubeflow), and large-scale data processing technologies, including hands-on familiarity with Docker, Kubernetes, and operating in cloud environments, especially AWS and Google Cloud.