Machine Learning Infrastructure Engineer - LLM & Agentic AI

Stellar Cyber

4h•$150,000 - $215,000

About The Position

Stellar Cyber is seeking a Machine Learning Infrastructure Engineer to build robust, scalable systems that power its Autonomous SOC applications. The role focuses on developing foundational AI infrastructure that enables intelligent agents to operate like SOC analysts in dynamic security operations environments. The engineer will help build agent frameworks, LLM inference infrastructure, MCP servers, and supporting API services for Stellar Cyber’s Open XDR platform, working closely with research, engineering, and product teams.

Requirements

Bachelor’s or Master’s degree in Computer Science or a related field, or equivalent practical experience.
At least 2 years of software development experience, or at least 1 year of software development experience with an advanced degree, in an industry setting.
At least 2 years of experience with data structures or algorithms in an academic or industry setting.
At least 2 years of experience developing backend infrastructure, distributed systems, REST or gRPC APIs, and microservices for MLOps-related projects.
Experience with cloud computing technologies, including containerization, orchestration, and deployment such as Docker and Kubernetes.
Experience with one or more of the following programming languages: Python, Java, or Go.

Nice To Haves

Experience working on LLM applications in high-sensitivity domains such as finance, defense, or health.
Experience with Generative AI frameworks such as LangChain, LangGraph, or AutoGen, and technologies such as prompt engineering, vector databases, and RAG.
Experience with observability practices in ML systems, such as metrics and cost tracking.
Experience deploying and scaling LLMs for inference using frameworks such as vLLM or llama.cpp.
Experience working on ML platform teams and/or building tools for researchers.
Knowledge of SecOps concepts, activities, and workflows.

Responsibilities

Design and build Agentic AI frameworks to orchestrate LLM-based agents that reason, plan, and execute SecOps tasks in Stellar Cyber’s Open XDR platform.
Design and develop scalable LLM inference infrastructure for 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 supporting API services for Autonomous SOC applications to provide reliable and extensible interfaces for agent operations.
Collaborate with machine learning and security researchers, UI, backend, and infrastructure engineers, and product management to align infrastructure with evolving product needs.