Machine Learning Infrastructure Engineer – LLM, Agentic AI

This is a fully remote position, open to applicants in United States.

📋 Description

• Create and develop Agentic AI frameworks to coordinate LLM-based agents that can reason, plan, and execute SecOps tasks within Stellar Cyber’s Open XDR platform.

• Design and implement scalable LLM inference infrastructure that ensures runtime and cost efficiency while managing resources across various LLM hosting providers.

• Build MCP servers that engage with the services and features of the Open XDR platform, integrating seamlessly with LLM-based agents.

• Develop supportive API services for Autonomous SOC applications to offer reliable and extensible interfaces for agent operations.

• Collaborate with machine learning and security researchers, user interface, backend, and infrastructure engineers, along with product management to ensure the infrastructure aligns with the evolving needs of the product.

⛳️ Requirements

• Bachelor’s or Master’s degree in Computer Science or a related discipline, or equivalent practical experience.

• 2 years of experience in software development or 1 year in an industry position with an advanced degree.

• 2 years of experience with data structures or algorithms in either an academic or industry context.

• 2 years of experience in creating backend infrastructure, distributed systems, APIs (REST / gRPC), and microservices for MLOps-related projects.

• Familiarity with cloud computing technologies, including containerization, orchestration, and deployment (Docker, Kubernetes, etc.).

• Proficiency in one or more of the following programming languages: Python, Java, Go.

• Prior experience working on LLM applications in high-sensitivity domains is preferred.

• Familiarity with Generative AI frameworks and technologies is preferred.

• Experience with observability practices in machine learning systems is preferred.

• Experience in deploying and scaling LLMs for inference using frameworks such as vLLM and llama.cpp is preferred.

• Previous experience on ML platform teams and/or developing tools for researchers is preferred.

• Knowledge of SecOps concepts, activities, and workflows is a plus.

🏝️ Benefits

• Pre-IPO Stock Options

• Medical, Dental & Vision care

• 401(k)

• Employee Assistance Program

• Employee Discount Program

• Life Insurance

• Paid time off

• Referral Program

• Rewards and Recognition Program

• Competitive salary

• Comprehensive benefits

• Ample career growth opportunities