Applied AI Engineer

Requirements:

• Built and shipped full-stack features across frontend, backend, and infrastructure, with demonstrated ownership from design through production operation.
• Worked with LLMs in production and formed real opinions from it.
• A working understanding of how to structure what an agent knows and can do within the constraints of a context window.
• Deep backend engineering fundamentals in a typed language.
• Built or operated systems with real security constraints.
• Delivered frontend experiences with a modern stack.
• Operated what you've built.

Nice to Haves:

• Designed tool interfaces or capability systems for AI agents.
• Worked with the Effect ecosystem or strongly-typed functional programming in TypeScript.
• Built multi-tenant platforms or systems with enterprise security requirements.
• Experience in Python library development or designing SDKs for programmatic consumption.
• Worked within Blockchain, compliance, or financial services domains.

What You'll Be Doing:

• Design and build the agent platform end to end.
• Own the skill architecture.
• Build and operate sandboxed execution environments.
• Ship full-stack features across frontend, backend, skill libraries, and infrastructure.
• Develop the workflow platform.
• Drive AI quality, cost, and observability.
• Raise the reliability and security bar for systems.

Perks and Benefits:

N/A - Perks and benefits section not provided in the job description.