About this role.
Jobber seeks a Director of Software Engineering to own the AI system layer across its product, including AI foundations, Copilot, automations, marketplace integrations, and emerging voice and messaging surfaces. The leader will manage approximately 30 engineers through four to six Engineering Managers or Senior Engineering Managers while partnering closely with Product, Design, and Data. The role requires deep experience building production LLM and agentic systems with orchestration, tool use, evaluation, observability, reliability controls, and safety guardrails. Success is defined by proactive, measurable, trusted AI workflows that improve how small home-service businesses schedule, follow up, communicate, invoice, and operate. This is a high-autonomy, fast-moving systems leadership role focused on organizational scale as well as technical strategy.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader CA market for similar roles.
Core skills
Skills and capabilities most closely associated with this opportunity.
Cover letter sample
Dear Hiring Team,
I am excited by the opportunity to lead Jobber’s evolution from isolated AI features to reliable, customer-centered AI workflows that proactively help service professionals run their businesses. My experience leading multi-team engineering organizations and production AI systems would enable me to set a clear technical strategy across orchestration, evaluation, safety, platform primitives, and workflow execution.
I bring a systems mindset, strong product partnership, and a practical approach to balancing speed, reliability, and responsible autonomy. I would welcome the opportunity to build an organization that helps Jobber deliver measurable, trustworthy intelligence at scale.
Sincerely,
Candidate
Sample interview questions
I would begin by mapping the highest-value customer journeys, current AI capabilities, dependencies, and failure modes. I would define shared primitives for context, tool access, identity, permissions, evaluation, observability, and guardrails, then sequence a small number of measurable workflow bets while establishing a platform roadmap that enables reuse.
I would use a layered evaluation approach: offline scenario suites for regressions, sandbox testing for tool execution, staged production releases, and online metrics tied to customer outcomes. I would also define clear escalation paths, human-review thresholds, audit logs, and rollback mechanisms for actions with material customer impact.
I would organize around durable customer or platform outcomes rather than individual features, with accountable engineering managers and explicit interface ownership. Shared architecture reviews, common metrics, and a regular operating cadence with Product, Design, and Data would keep teams aligned without centralizing every decision.
I would evaluate autonomy by the reversibility of actions, customer impact, confidence signals, and quality of available context. Low-risk, reversible actions can be automated earlier, while high-impact actions should start with recommendations, approvals, or constrained execution until performance and trust are established.
I would connect technical metrics to user and business outcomes, such as task completion, time saved, conversion improvement, follow-up effectiveness, error rates, and customer trust. I would require each workflow to have a baseline, target, instrumentation plan, and qualitative feedback loop so teams learn whether the intelligence is genuinely helpful.
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
WHAT WE’RE LOOKING FOR
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 (non-negotiable)
You’ve built or led production LLM/agentic systems.
You understand what actually works (and what doesn’t)
You’ve seen systems fail and improved them
You have opinions about evaluation, reliability, and safety
Execution
You can move fast without breaking everything.
You’ve balanced shipping vs infrastructure vs tech debt
You know when to iterate and when to redesign
WHY JOBBER · WHY NOW?
This is not “AI theatre.”
We already have:
AI Receptionist (live, handling real customer calls)
AI features embedded across the product
250,000+ businesses using the platform
What we don’t have yet is: A unified, intelligent system across the product.
That’s what this role builds.
TLDR:
Most Director roles optimize delivery. This one defines: How an entire product becomes intelligent.
Compensation:
At Jobber, we also believe that compensation should be transparent, fair, and supportive of your experience and growth. This role has a minimum annual salary of $221,800 CAD, a midpoint of $261,000 CAD, and a maximum salary of $300,100 CAD, designed to reflect the progression from learning the ropes to truly excelling.
We design our compensation to reflect each new hire’s skills, experience, and the complexity of the role, ensuring a fair and competitive salary. Our range is intentionally broad to support growth and long-term impact, with fully established hires typically starting around the midpoint. The higher end of the range is reserved for those who have demonstrated deep expertise and lasting contributions, while offers below the midpoint reflect strong potential with room to develop. This approach ensures that compensation aligns with both an individual’s current capabilities and their opportunity for future growth.
We believe in transparency and open conversations about compensation. If you have any questions about our approach, we’re happy to discuss them throughout the hiring process!
What you can expect from Jobber:
A total compensation package that includes an extended health benefits package with fully paid premiums for both body and mind, matching in RRSP, TFSA or FHSA, and stock options.
A dedicated Talent Development team and access to coaching, learning, and leadership programs to help you grow your career, reach your goals, and unlock your full potential.
A unique opportunity to build, grow, and leave your impact on a $400-billion industry that has no dominant player…yet.
To work with a group of people who are humble, supportive, and give a sh*t about our customers.
We believe that diverse teams perform better and that fostering an inclusive work environment is a key part of growing a successful team. We welcome people of diverse backgrounds, experiences, and perspectives. We are an equal opportunity employer, and we are committed to working with applicants requesting accommodation at any stage of the hiring process.
A bit more about us:
Job by job, we’re transforming the way service is delivered. Your lawn care provider, home cleaning service, plumber or painter could use Jobber to better connect with their customers, save time in the office, invoice faster, and get paid! We’re bringing tens of thousands of people together with technology to deliver billions of dollars a year in services to happy customers. Jobber exists to help make these small businesses successful, and when they’re successful we all win!
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