About the job
Join Our Team
At Prophet Security, we are pioneering a revolutionary platform designed to streamline complex security operations. Our mission is to empower engineers to directly influence customer outcomes. As part of our innovative team, you will engage closely with clients, grasp their needs, and witness the real-world impact of your contributions. If you thrive in a dynamic startup environment and are passionate about creating meaningful products, we invite you to apply!
With over 30 years of collective experience in the cybersecurity domain, our founding team has held leadership roles at renowned organizations such as Abnormal Security, Expel, Mandiant, McAfee, Oracle, Red Canary, Red Hat, Riverbed, and Symantec. We are dedicated to transforming the expansive $400 billion security labor market.
About Our Platform
Our platform serves as a catalyst for security teams, analyzing alerts, formulating and executing investigation strategies, and delivering comprehensive findings along with actionable insights. Analysts provide essential feedback, which is integrated into ongoing investigations, fostering an evolving and responsive security approach. Our objective is to fundamentally alter the balance of power in cybersecurity, favoring defenders.
Your Role
As a pivotal member of our founding AI Engineering team, you will influence the architecture and technical direction of our next-generation Agentic AI SOC Platform. This role focuses on developing artificial intelligence and machine learning capabilities that power our product, with an emphasis on large language models (LLMs) and AI agents.
Key Responsibilities
- Architect, design, and implement our Agentic AI platform.
- Enhance LLM performance on security-specific tasks through in-context learning, prompt engineering, and retrieval-based context augmentation techniques.
- Drive the architecture of machine learning solutions, making informed decisions regarding model configurability, portability, and cost considerations.
- Establish evaluation methodologies, guidelines, metrics, and infrastructure to assess the performance of our machine learning systems.
- Collaborate with cross-functional teams to align technical objectives with business needs.
