Staff Engineer, Agent Systems - Durable Automation

Human Intuition Inc.

New York (NY)

On-site

USD 150,000 - 190,000

Full time

14 days+
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Job summary

Human Intuition Inc. is hiring to build the runtime between models and business software, managing execution state, tools, permissions, memory, and recovery. The role focuses on creating agents that are useful, understandable, and controllable across distributed systems.

You will own a problem from design through deployment, developing durable workflows and tool integrations with strong error reporting and observability.

Qualifications

  • Experience operating backend or distributed systems.
  • Fluency in Python or TypeScript.
  • Experience with agents, workflow engines, or async systems.
  • Ability to own a problem from design to deployment.

Responsibilities

  • Build durable execution for multi-step workflows with external services and interruptions.
  • Design tool interfaces and integrations with clear contracts and scoped permissions.
  • Implement checkpointing, retries, cancellation, idempotency, and recovery without duplicating actions.
  • Develop context and memory systems preserving information and provenance across tasks.
  • Make traces inspectable and replayable for researchers and operators to diagnose failures.
  • Connect production experience to evaluation and learning systems and turn research into dependable capabilities.

Skills

Backend systems
Distributed systems
Python
TypeScript
Asynchronous systems
State management
Access control
Deployment ownership

Tools

Workflow engines
Tracing/observability
Browser automation

Job description

Human Intuition Inc. is hiring to build the runtime between models and business software, managing execution state, tools, permissions, memory, and recovery. The role focuses on creating agents that are useful, understandable, and controllable across distributed systems.

You will own a problem from design through deployment, developing durable workflows and tool integrations with strong error reporting and observability.

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