Director, Software Engineering (AI Workflows & Ecosystem)

Jobber

1d

About The Position

Jobber is seeking a Director of Software Engineering to lead the transformation of its AI capabilities from fragmented features into a unified, intelligent system across the entire product. This role is crucial for evolving Jobber into an AI-powered business operations platform, moving beyond individual AI features to intelligent workflows and proactive business management for service professionals. The ideal candidate will own the end-to-end AI system layer, encompassing AI foundations, user-facing intelligence (Copilot), workflow execution, ecosystem integrations, and emerging AI surfaces. This is a strategic leadership position focused on building systems that remove cognitive load from busy small business owners, enabling them to focus on their core services rather than managing software.

The target customer is a small business owner, such as a plumber, cleaner, or landscaper, who is time-poor and needs the platform to proactively guide their actions and provide insights. They are looking for answers to questions like "What should I do next?" or "Why didn't this job convert?", with the ultimate goal being a system that anticipates their needs without them having to ask. The Director will be responsible for defining the AI vision across Jobber, building and evolving a multi-team organization (approximately 30 engineers across 4-6 teams, with 4-6 Engineering Managers/Sr. EMs reporting to them), and fostering close partnerships with Product, Design, and Data teams. Success will be measured not by shipping AI features, but by the system proactively recommending and taking actions, teams building on shared AI primitives, reliable and improving AI output, and customers feeling the product actively works for them.

Requirements

• Experience building real systems where AI makes decisions and takes actions in production.
• Experience with agent orchestration (not just prompts).
• Experience with tool use and workflow execution.
• Experience with evaluation (offline and online).
• Experience with observability and failure handling in AI systems.
• Experience with guardrails and safety in real-world AI systems.
• Understanding of tradeoffs between autonomy and control in AI systems.
• Ability to reason at the system level, even if not coding daily.
• Leadership experience managing organizations through complexity, not just growth.
• Experience managing managers across multiple teams.
• Experience building organizations that scale.
• Experience driving cross-org alignment in ambiguous spaces.
• Systems thinking, not just feature thinking.
• Understanding of how user workflows connect end-to-end.
• Deep partnership experience with Product and Design teams.
• A focus on customer outcomes over technical output.
• Experience building or leading production LLM/agentic systems.
• Understanding of what AI approaches actually work and what doesn't.
• Experience seeing AI systems fail and improving them.
• Informed opinions about AI evaluation, reliability, and safety.
• Ability to move fast without breaking everything.
• Experience balancing shipping features, infrastructure development, and managing technical debt.
• Knowledge of when to iterate and when to redesign.

Nice To Haves

• Experience rolling out Copilot internally.
• Experience using LLM APIs for features.
• Experience in a role adjacent to AI.

Responsibilities

• End-to-end ownership of Jobber’s AI system layer, ensuring intelligence flows across the entire product.
• Owning AI Foundations, including models, orchestration, evaluations, and guardrails.
• Developing and evolving the Copilot (user-facing intelligence layer).
• Building and managing the Automations (workflow execution layer).
• Overseeing the Platform Experience / Marketplace for AI integrations and ecosystem development.
• Exploring and developing emerging AI surfaces like voice and messaging.
• Defining how decisions are made within the AI system.
• Ensuring context moves effectively across workflows.
• Managing how actions are triggered and when they should not be.
• Establishing methods for evaluating AI performance and effectiveness.
• Implementing agentic workflows (reason → decide → act → evaluate).
• Ensuring cross-product context is leveraged (jobs, customers, payments, communication).
• Addressing reliability, safety, and failure modes of AI systems.
• Improving the developer experience for building on top of AI systems.
• Defining the overall AI strategy for Jobber.
• Building and evolving a multi-team organization to execute the AI vision.
• Making strategic tradeoffs between speed, quality, and safety.
• Driving adoption of AI system thinking across engineering, product, and the company.
• Challenging assumptions and pushing teams beyond feature-level thinking to system-level thinking.

Benefits

• Extended health benefits package with fully paid premiums for both body and mind
• Matching in RRSP, TFSA or FHSA
• Stock options
• Access to a dedicated Talent Development team
• Access to coaching, learning, and leadership programs

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed