- Location
- United States · published
- Type
- Full-time
- Department
- Engineering
- Source
- Workable
Description
Join a fast-growing global leader in cybersecurity, trusted by some of the biggest names in the industry. In addition to some of the world’s largest enterprises and government agencies, more than 30% of the world’s top MSSPs rely on our platform. We’re at the forefront of protecting organizations against sophisticated cyber threats using cutting-edge AI and automation technologies. Our culture is built on diversity, openness, and collaboration, fostering creativity and innovation that drives real impact in the market.
We are looking for a highly skilled Machine Learning Infrastructure Engineer with a passion for building robust and scalable systems to power Stellar Cyber’s Autonomous SOC applications. In this role, you will be at the forefront of AI infrastructure innovation, responsible for developing the foundational components that enable intelligent agents to work like true SOC analysts to operate in dynamic SecOps environments.
Responsibilities
- Design and build Agentic AI frameworks to orchestrate LLM-based agents capable of reasoning, planning, and executing SecOps tasks in Stellar Cyber’s Open XDR platform.
- Design and develop scalable LLM inference infrastructure that supports runtime- and cost-efficient serving and resource management across LLM hosting providers.
- Develop MCP servers that interact with Open XDR platform services and features, and integrate with LLM-based agents.
- Develop other supporting API services necessary for Autonomous SOC applications to provide reliable and extensible interface for agent operations.
- Collaborate closely with machine learning / security researchers, UI / backend / infrastructure engineers, and product management to align infrastructure with evolving product needs.