Director, Software Engineering (AI Workflows & Ecosystem)

Requirements

• Leadership
• You've led orgs through complexity, not just growth.
• Managed managers across multiple teams
• Built organizations that scale (not just teams that ship)
• Driven cross-org alignment in ambiguous spaces
• Product + Systems Thinking
• You think in systems, not features.
• You understand how user workflows connect end-to-end
• You've partnered deeply with Product and Design
• You care about customer outcomes, not just technical output
• AI Depth (no

Benefits

Additional Information

Are you driven to bring people, technology, and strategy together to build impactful software? Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber, they can quote, schedule, invoice, and collect payments from their customers while providing an easy and professional customer experience. Running a small business today isn't like it used to be-the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That's why we put the power and flexibility in their hands to run their businesses how, where, and when they want! 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 This role owns that shift. Not a team. Not a feature. The system. 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 Director who succeeds here will understand: This isn't about building clever systems; it's about building systems that remove thinking from already overwhelmed people. WHAT YOU'D OWN End-to-end ownership of Jobber's AI system layer. You're not owning a single team. You're owning how intelligence flows across the entire product. Product + Platform Scope 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 This includes: Agentic workflows (reason → decide → act → evaluate) Cross-product context (jobs, customers, payments, communication) Reliability, safety, and failure modes Developer experience for building on top of AI systems Team Structure ~30 engineers across 4-6 teams 4-6 EMs / Sr EMs reporting into you Close partnership with Product, Design, Data WHAT "GOOD" LOOKS LIKE Not "we shipped AI features." Instead: The system proactively recommends and takes actions Teams build on shared AI primitives, not reinventing them AI output is reliable, measurable, and improving over time Engineers trust the system, and move faster because of it Customers feel like the product is working for them , not just responding 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. That means 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 You don't need to code daily, but you must be able to reason at the system level. 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

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