Machine Learning Infrastructure Engineer (AI)

Location: Remote, United States

Salary: USD 150,000–215,000 per year, plus bonus opportunity and equity.

Company

hirify.global develops an AI-powered Open XDR cybersecurity platform used by enterprises, government agencies, and managed security service providers.

What you will do

• Design and build agentic AI frameworks that orchestrate LLM-based agents for reasoning, planning, and execution of SecOps tasks.
• Develop scalable LLM inference infrastructure for runtime- and cost-efficient serving and resource management across hosting providers.
• Build MCP servers that interact with Open XDR services and features and integrate with LLM-based agents.
• Develop reliable and extensible API services for Autonomous SOC applications.
• Collaborate with machine learning and security researchers, UI, backend, and infrastructure engineers, and product management.

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 1 year 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, containerization, orchestration, and deployment technologies such as Docker and Kubernetes.
• Experience with one or more of Python, Java, or Go.

Nice to have

• Experience developing 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 including prompt engineering, vector databases, or RAG.
• Experience with ML-system observability, including metrics and cost tracking.
• Experience deploying and scaling LLM inference with frameworks such as vLLM or llama.cpp.
• Experience working on ML platform teams or building tools for researchers.
• Knowledge of SecOps concepts, activities, and workflows.

Culture & Benefits

• Collaborative, diverse, and open culture focused on cybersecurity innovation, creativity, and product impact.
• Pre-IPO stock options, bonus opportunity, and equity.
• Medical, dental, and vision care; life insurance; 401(k); and an Employee Assistance Program.
• Paid time off, employee and referral programs, and rewards and recognition.
• Career growth opportunities within a fast-growing AI and cybersecurity organization.