Staff Software Developer, Full Stack

Come join the Intuit Toronto site as a Staff Software Developer. Be a leader in our VEP Sales Partners and Incentives team that is building an AI powered robust Partner Platform that unifies sales motions across Mid-Market and Mass Market for QB, MC, Accountants, and Credit Karma with AI powered automation and intelligence to deliver growth at scale.
The ideal candidate is an experienced Software Developer who is experienced with Java, TypeScript, React and general full-stack development. This engineer should be full-stack and prepared to work at all levels of the application. They will be directly responsible for the design, development, testing, maintenance, and documentation of high-volume customer experiences.
Intuit has embraced a hybrid working model and this role will be based out of our Toronto office 3 days per week.

Responsibilities
Drive significant technology initiatives end-to-end and across multiple layers of architecture
Architect and develop scalable applications or systems
Drive the design and implementation of durable and software solutions to solve critical customer problems that are scalable, secure, easy to maintain, and interact with numerous other systems
Provide recommendations and best practices for application development, platform development, and developer tools
Actively stay abreast of industry best practices, share learnings, and experiment and apply cutting edge technologies
Provide/inspire innovations that fuel the growth of Intuit as a whole and generate creative ideas for emerging business needs
Partner and work with global teams across time zones
Communicates clearly, succinctly, and persuasively to all levels of employees, customers, and management (including executives)
Proactively identify opportunities to enhance software applications with AI technology
Coach and mentor junior engineers on best practices of software engineering, leveraging AI to enhance applications, and building their technical expertise to ensure efficient and effective outcomes
Launch AI integrations in production and evaluate their impact on software performance and user satisfaction, using appropriate metrics

Qualifications
BS/MS in Computer Science or related area or equivalent experience.
7+ years of total experience delivering enterprise-class applications.
Solid foundation in writing scalable application code following best practices of accessibility, internationalization, and instrumentation.
Experience with cross-browser, cross-platform, and design constraints on the web and mobile.
Solid knowledge of algorithms and design patterns.
Proficiency with JavaScript application design and testing experience.
Proficiency in mid-tier languages like Java.
Experience with test automation: TDD, unit/integration/functional testing.
Experience with Relational Database Design and Implementation.
Interest in building CI/CD pipelines.
Practical experience in developing applications using microservices, container technologies, container management systems such as Kubernetes, Mesos, etc.
Strong experience with Databases design (SQL, NoSQL) and analytics.
Prior working experience in utility computing and/or cloud computing domain.
Experience building and deploying applications and services into cloud environments.
Possesses an in-depth understanding of AI integration and can lead the integration process effectively, while coaching junior engineers on how to leverage AI
Ability to work collaboratively with cross-functional teams, including data scientists, product managers, and software engineers.

Footer Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.