LLM Agent Engineer - Specialist

Obsidian

Toronto

On-site

CAD 120,000 - 180,000

Full time

14 days+
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Job summary

Obsidian is seeking engineers to build and operate LLM agents in production. You will ship agents used by real users, and be on the hook when they break, with visibility into impact and cost.

We value experience in production-grade agent systems, long-running jobs, and measuring improvement, adoption, and tradeoffs in real deployments. Apply with stories about your war-time fixes and lessons learned.

Qualifications

  • Shipped an agent that real users depended on.
  • Figured out how to tell whether an agent got better or worse after a change.
  • Run agents that outlive a single request: scheduled jobs, long-running work, cloud sandboxes.
  • Watched your org build an internal assistant and seen adoption patterns.

Responsibilities

  • Build and operate LLM agents in production.
  • Ensure reliability, observability, and cost visibility of agents.
  • Collaborate with teams to improve adoption and impact of agents.

Skills

Agent development
LLM integration
Production deployment
Performance evaluation

Job description

We are looking for engineers who build and operate LLM agents in production, and who have real visibility into how agents are actually used inside a company.

You have probably:

  • Shipped an agent that real users depended on, and been on the hook when it broke.
  • Figured out how to tell whether an agent got better or worse after a change.
  • Run agents that outlive a single request: scheduled jobs, long-running work, cloud sandboxes.
  • Watched your org build an internal assistant, and seen who adopted it and who quietly did not.

We are especially interested in the layers most people do not talk about: internal monoagents wired into company data, shared company memory, reusable skills and playbooks, the tool and MCP surfaces agents call, and how anyone sees what agents did and what they cost.

Applying starts with a short conversational AI interview. No coding, no take-home. We want to hear how you actually think about agent reliability, evaluation, and adoption, and the tradeoffs you have made in real systems. Bring war stories. The messier and more specific, the better.

If that screen stands out, we will invite you to a live 30 minute conversation with our team. We pay $100 to $500 for that conversation, paid on completion of the call, with the amount depending on depth of experience.

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