Homebase

Android Engineer II (Hybrid)

Toronto · Mid

Sponsorship not specifiedDetected 21 days ago

JavaKotlinAndroidJetpack ComposeCode ReviewGitCircleCIRESTUI DesignJiraRecruitingCommunicationCollaborationProblem Solving

About the role

At Homebase, you'll join a team that's bold, fast-moving, and obsessed with helping small businesses thrive.
This is a unique opportunity to shape customer experiences that directly influence growth while helping define how modern AI-enabled product development operates at Homebase.
Experience comes in many forms-so if you're excited about this role, even if you don't meet 100% of the qualifications, we encourage you to apply!

Develop clean, scalable, testable Kotlin code that raises the bar for mobile engineering quality.
Partner with backend engineers, product and design to deliver AI-powered signup, onboarding, and team activation experiences.
Collaborate cross-functionally with backend, web, data, and AI platform partners to ensure seamless end-to-end system behavior.
Advanced understanding of object-oriented design patterns and their application within Android frameworks
We build with empathy, act with urgency, and take big swings that drive real-world impact.
Here, every Homie shows up to raise the bar, support one another, and celebrate wins as a team.
We're not just building an app-we're building unstoppable teams.
Working primarily in Kotlin while collaborating closely with backend engineers, Product, Design, and Data teams, you'll identify opportunities, ship experiments, and build seamless mobile experiences that improve customer outcomes.
Deep knowledge of Android UI design principles, patterns, and best practices
That means you'll have access to paid AI tools with minimal restrictions, so you can build, experiment, and level up your craft.

Strong experience with Jetpack Compose and modern Android UI frameworks
Strong understanding of performance optimization for mobile applications
Experience with RESTful APIs and third-party integrations
Experience with testing frameworks (unit, feature, integration)
That's why Tuesday and Wednesday are our required in-office days-a time to move faster as a team, build deeper connections, make better decisions, and build together.

Strong systematic thinking and problem-solving skills
Demonstrated curiosity and hands-on experience using AI tools to streamline workflows, debug, generate tests, and improve development velocity
💡 Be Customer Obsessed - Solve problems with empathy and creativity.
⚡ Move Fast, Learn Fast - Experiment, take action, and grow every day.
🏆 Master Your Craft - Excellence fuels impact-show up, step up, and make your mark.
Java, RxJava, Firebase, Room, Retrofit, Navigation 3, Compose Destinations, multi-module architecture
🤝 The Homie Way - These principles guide everything we do-from how we work and make decisions to how we show up for each other.
🤖 AI access, for real: We invest in builders and believe that curiosity shouldn't have a paywall.

💰 Ownership & Savings: Stock options + TFSA/RRSP with 4% company match
🏥 Health & Wellness: Comprehensive medical, dental, and vision for you and your dependents
⏰ Paid Time Off: Flexible PTO + company holidays + designated focus periods
👶 Family Support: Maternity/Parental Leave EI top-up support offered (after 6 months of service)
🛡️ Protection Plans: Life insurance + short/long-term disability coverage
🍽️ Workspace Perks: Meals provided, team offsites, and Customer Days

Build, ship, and maintain Android features in the onboarding and activation flows that help new customers reach value faster.
We're looking for an Android Engineer II who thrives at the intersection of product thinking, engineering execution, and experimentation.
You'll independently own Android-first product and growth initiatives that help customers discover value faster, engage more deeply, and get more from Homebase.
💜 Belonging at Homebase - We're committed to fostering a welcoming space where every Homie can be their full self.

This listing is sourced directly from Homebase's careers page and normalized into a canonical job model.