We're building the integration layer for AI inside a fintech's collaboration platform.

Four engineers. Brand recent team. First crack at wiring collaboration tooling into an AI SDLC - not a legacy system to patch, a layer to define.

What you own

- MCP servers, exposed by the collaboration stack, that let agents reach real domain objects instead of just talking.
- Bots that are actually agents - tool-calling, knowledge-grounded, wired into internal systems that matter.
- The pipelines and domain-object boundaries a much larger AI platform team builds on top of.

What you bring

- Java depth. Not exposure - depth . You make the right call on a Java system without being taught its intricacies.
- Integration instinct. HubSpot, Salesforce,



Atlassian - the vendor doesn't matter. Knowing how to integrate cleanly with a third-party system does.
- Discovery before code. You ask what needs to be built before you build it, and you design it structured, not sprawling.
- Enough AI fluency to grow fast into MCPs, skills, and agents. You don't need to be there yet. You need to actually want to be.

No Jira or Atlassian background required here. A strong generalist with real integration judgment beats a specialist in one vendor's stack.

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📌 Senior Back End Engineer (Sydney)
🏢 Tekfinder
📍 Sydney