Founding AI Infrastructure Engineer

Harden; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Harden is seeking an engineer to build the foundations for AI-powered workflows, moving from prototypes to dependable production services. The role spans distributed and machine-learning systems, cloud infrastructure, performance, and platform design, with a focus on operating securely inside customer-controlled environments.

You will develop core platform components, design APIs for integration, improve speed and reliability, and establish observability and deployment support that connects with

Qualifications

• Experience building distributed systems and production software platforms.
• Familiarity with machine-learning systems and AI-powered workflows.
• Experience with Kubernetes and cloud infrastructure.

Responsibilities

• Develop core platform components for execution, runtime, and AI model and data pipelines.
• Design APIs and integration points that fit into customers' existing systems and processes.
• Improve system speed, resilience, and ability to scale reliably.
• Build observability and operational foundations for production use.
• Support deployments that connect with customer infrastructure such as private clouds, pipelines, identity, security monitoring, and compliance workflows.

Skills

Distributed systems

Production software

Machine-learning systems

AI-powered workflows

Kubernetes

Cloud infrastructure

Performance engineering

Security engineering

Platform design

Job description

Role overview

Build the engineering foundations that move AI-powered workflows, including agent-based systems, from early prototypes into dependable production services. The role spans distributed and machine-learning systems, cloud infrastructure, performance, and platform design, with a focus on operating securely inside customer-controlled environments.

Responsibilities

• Develop core platform components for execution, runtime, and AI model and data pipelines.
• Design APIs and integration points that fit into customers' existing systems and processes.
• Improve system speed, resilience, and ability to scale reliably.
• Build observability and operational foundations for production use.
• Support deployments that connect with customer infrastructure such as private cloud networks, delivery pipelines, identity systems, security monitoring, ticketing, and compliance workflows.

Requirements

• Experience building distributed systems and production software platforms.
• Familiarity with machine-learning systems and AI-powered workflows.
• Experience with Kubernetes and cloud infrastructure.
• Ability to engineer for performance, reliability, and security.
• Skill designing platforms that integrate with complex enterprise environments.