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Salary: CAD 221,800 - 300,100 / annual
Jobber is a platform helping small home service businesses (plumbers, painters, landscapers) manage their operations through technology. They handle quoting, scheduling, invoicing, and payments for 250,000+ businesses.
This Director role owns end-to-end responsibility for Jobber's AI system layer—not a single team or feature, but how intelligence flows across the entire product. You will lead approximately 30 engineers across 4–6 teams, with 4–6 Engineering Managers reporting to you.
The core problem: Jobber has AI in production (AI receptionist, embedded features), but the systems remain fragmented. Service professionals still manually follow up on jobs, piece together context across workflows, and decide what to do next. The platform doesn't yet think across the product or proactively help them run their business.
Your scope includes:
- 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)
You are responsible for how decisions get made inside the system, how context moves across workflows, how actions get triggered, and how we evaluate whether AI is actually working. This includes agentic workflows (reason → decide → act → evaluate), cross-product context (jobs, customers, payments, communication), reliability, safety, and failure modes, and developer experience for building on top of AI systems.
Success means the system proactively recommends and takes actions, teams build on shared AI primitives rather than reinventing them, AI output is reliable and measurable, engineers trust the system and move faster, and customers feel the product is working for them.
You will define how AI should work across Jobber, build and evolve a multi-team org to execute that vision, make tradeoffs between speed, quality, and safety, push teams beyond feature thinking into system thinking, challenge assumptions, and drive adoption across engineering, product, and the company.
You will partner closely with Product, Design, and Data teams.
REQUIREMENTS:
- Leadership: Managed managers across multiple teams; built organizations that scale (not just teams that ship); driven cross-org alignment in ambiguous spaces.
- Product + Systems Thinking: Think in systems, not features; understand how user workflows connect end-to-end; partnered deeply with Product and Design; care about customer outcomes, not just technical output.
- AI Depth (non-negotiable): Built or led production LLM/agentic systems; understand what actually works and what doesn't; seen systems fail and improved them; have opinions about evaluation, reliability, and safety. 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, and tradeoffs between autonomy vs. control. Must be able to reason at the system level (coding daily not required).
- Execution: Balanced shipping vs infrastructure vs tech debt; know when to iterate and when to redesign; can move fast without breaking everything.
