AI Harness Engineer

About the role

Armis is developing the infrastructure required to run AI agents securely and reliably at scale. This position focuses on the backend systems, control planes, and developer tools that support production-grade AI, rather than model training or machine learning research.

Key facts

What you'll do

• Architect and construct secure infrastructure to support production AI agents.
• Create Agent Control Plane features to manage, monitor, and secure agent execution.
• Integrate security mechanisms and embedded controls directly into AI agents.
• Build and maintain APIs, reusable services, and developer tooling.
• Manage integrations with Model Context Protocol and various Agent SDKs.
• Develop backend microservices using Python and AWS.
• Implement observability, telemetry, and tracing for AI systems.
• Create CLI tools and public-facing developer interfaces.
• Transition prototypes from researchers into production environments.
• Lead technical projects from initial design to deployment.

Requirements

• 5+ years of experience in backend software engineering.
• Professional experience building AI Harnesses.
• Professional experience with AI security and harness implementation.
• Advanced proficiency in Python.
• Proven track record of building microservice architectures and distributed systems.
• Experience with AWS cloud services.
• Hands-on experience developing AI agents, applications, or agentic workflows.
• Familiarity with Agent SDKs and Model Context Protocol.
• Experience creating CLI applications or developer-focused APIs.
• Ability to own projects independently within a startup-style environment.

Nice to have

• Experience designing Agent Control Planes or AI observability platforms.
• Background in security engineering or infrastructure engineering.
• Experience with AI governance, runtime guardrails, or policy enforcement.
• Practical experience deploying LLMs in production.
• Familiarity with Kubernetes and container orchestration.
• Experience integrating AI systems with cloud-based infrastructure.

Skills & tools

• Python
• AWS
• Microservices
• Agent SDKs
• Model Context Protocol
• CLI Development
• Distributed Systems
• AI Observability

Practical notes

This is a remote-friendly role based in the US. The compensation package includes base salary, performance bonuses, and equity in the form of RSUs. Applicants should be prepared to demonstrate experience in transitioning AI prototypes into stable, production-ready backend systems.