Director, Software Engineering (AI Workflows & Ecosystem)

THE PROBLEM YOU’D OWN

Jobber has AI in production, but not yet at its full potential. We already have AI answering calls, drafting responses, and powering parts of our product. But today, those systems are still fragmented. Some teams are ahead. Others aren’t. Some workflows are intelligent. Others are still manual. And most importantly, the system doesn’t yet think across the product.

A service pro still has to:

• Manually follow up on jobs
• Piece together context across workflows
• Decide what to do next

The platform doesn’t proactively help them run their business. That’s the gap. The opportunity is to evolve Jobber from:

• AI-powered features
• AI-powered workflows
• AI-powered business operations

THE CUSTOMER

You’re building for people who don’t have time to think about software. A plumber finishing their last job at 6 pm
A cleaner managing 30 clients and 5 employees
A landscaper juggling scheduling, payments, and follow-ups

They’re not asking for “AI.” They’re asking:

• “What should I do next?”
• “Why didn’t this job convert?”
• “Who should I follow up with today?”
• And eventually: “They shouldn’t have to ask at all.”

THE AI BAR (THIS ROLE IS DIFFERENT)

We are not looking for:

• Someone who rolled out Copilot internally
• Someone who used LLM APIs for features
• Someone adjacent to AI

We are looking for someone who has:

• Built real systems where AI makes decisions and takes actions in production
• Experience with:
• Agent orchestration (not just prompts)
• Tool use and workflow execution
• Evaluation (offline + online)
• Observability and failure handling
• Guardrails and safety in real systems
• Tradeoffs between autonomy vs. control

WHAT YOU’D OWN

End-to-end ownership of Jobber’s AI system layer.

• AI Foundations (models, orchestration, evals, guardrails)
• Copilot (user-facing intelligence layer)
• Automations (workflow execution layer)
• Platform Experience / Marketplace (integration + ecosystem surface)
• Emerging surfaces (voice, messaging, cross-product intelligence)

WHAT THIS ACTUALLY MEANS

You are responsible for:

• How decisions get made inside the system
• How context moves across workflows
• How actions get triggered (and when they shouldn’t)
• How we evaluate whether AI is actually working

WHAT YOU’LL ACTUALLY DO

• Define how AI should work across Jobber, not just within a team
• Build and evolve a multi-team org to execute on that vision
• Make tradeoffs between speed, quality, and safety
• Push teams beyond feature thinking into system thinking
• Challenge assumptions, including leadership’s
• Drive adoption across engineering, product, and the company