Senior Engineer (AI)

Location: Hybrid in North Carolina, United States

Company

hirify.global develops data services and engineering infrastructure, including AI and distributed computing platforms.

What you will do

• Lead the architecture, technical direction, and execution of the Harness & Loop Engineering platform.
• Build AI-powered development environments, agentic engineering sandboxes, inference orchestration platforms, and automated quality engineering systems.
• Define evaluation frameworks, validation pipelines, testing strategies, and guardrails for AI-assisted software development.
• Oversee GPU infrastructure, inference services, and Infinia cluster operations supporting AI development and testing.
• Guide the transition of internally validated engineering platforms into scalable, customer-facing products.
• Mentor engineers, conduct technical interviews, and collaborate with software engineering, AI research, platform, quality engineering, and product teams.

Requirements

• 12+ years of software engineering experience with technical leadership in large-scale distributed systems.
• Bachelor’s degree in computer science, computer engineering, software engineering, or a related technical discipline; a master’s degree is preferred.
• Experience designing AI-assisted software development platforms or developer productivity tooling.
• Deep expertise in machine learning infrastructure, LLM inference serving, distributed AI systems, agentic systems, and inference orchestration.
• Hands-on experience managing GPU clusters, AI compute infrastructure, or large-scale distributed computing environments.
• Strong knowledge of software architecture, CI/CD, automated testing, validation, production lifecycle management, and engineering leadership.

Nice to have

• Experience productizing internal engineering platforms for external customers.
• Knowledge of model serving frameworks, high-performance computing, observability, and platform reliability.
• Familiarity with storage systems, distributed data platforms, or enterprise AI infrastructure.
• Contributions to open-source developer platforms, AI tooling, or infrastructure projects.

Culture & Benefits

• Focus on improving software development through engineering platforms and AI-assisted workflows.
• Emphasis on architectural quality, scalability, operational excellence, correctness, reliability, and security.
• Collaborative technical leadership across engineering, AI research, quality engineering, and product management.
• Opportunity to transform internal innovation into production-ready customer capabilities.