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Director, Software Engineering (AI Workflows & Ecosystem)

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19 Oct 2026Apply before
Opportunity details

About this role.

AI Summary

Jobber is hiring a Director of Software Engineering to lead the company’s AI workflow and ecosystem strategy across product and platform surfaces. The role manages roughly 30 engineers through 4–6 engineering managers and is accountable for AI foundations, agent orchestration, evaluations, guardrails, automations, and developer experience. This leader will unify currently fragmented AI capabilities into reliable, proactive systems that can recommend and execute actions for home-service businesses. Success requires deep production experience with LLM or agentic systems as well as strong multi-team organizational leadership and product partnership. The role emphasizes measurable customer outcomes, safety, reliability, and thoughtful tradeoffs between autonomy and control.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a high-complexity leadership role spanning an organization of managers and engineers while defining a cross-product AI systems strategy. It requires proven judgment in production agentic AI, safety and reliability practices, organizational design, and executive-level cross-functional alignment.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$250,000
US market range$210k–$310k
AI insightNo salary range is disclosed; the stated total-compensation elements are benefits and stock options rather than salary. Estimated US annual base-salary market range for a Director of Software Engineering leading AI/agentic platform teams is $210,000–$310,000 USD, with an estimated midpoint of $250,000 USD; total compensation may be higher when equity and bonuses are included.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
Describe a production agentic AI system you led. How did it reason, use tools, and handle failed actions?

I would explain the system’s decision boundaries, available tools, approval model, and orchestration architecture. I would also describe observability, retries, fallbacks, human escalation paths, and the outcome metrics used to validate that autonomous actions were safe and valuable.

How would you create a shared AI platform when teams already have fragmented AI features?

I would first inventory existing use cases, models, data dependencies, and quality gaps. Then I would establish common primitives for context, tool access, evaluation, telemetry, permissions, and guardrails, migrate high-value workflows incrementally, and publish clear adoption standards for product teams.

How do you determine when an AI workflow should act autonomously versus request user confirmation?

I use a risk-based framework that considers reversibility, customer impact, confidence, permissions, and the cost of an incorrect action. Low-risk, reversible actions can be automated, while consequential or uncertain decisions should require confirmation or route to a human review path.

What metrics would you use to evaluate an AI-powered workflow for service-business customers?

I would combine model-quality metrics such as task success, groundedness, tool-call accuracy, and failure rate with customer and business outcomes such as time saved, follow-up completion, conversion, payment collection, retention, and user override rates. Metrics should be segmented by workflow, customer cohort, and confidence level.

How have you led managers through a major technical and organizational shift?

I set a clear operating vision and measurable outcomes, define ownership boundaries, and equip managers to communicate the change locally. I create regular decision forums, address capability gaps through hiring or development, and use milestones and transparent metrics to maintain alignment while allowing teams flexibility in execution.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.

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.

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!

Apply now >

This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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