Software Engineer I

3 days ago

Toronto ON, Toronto Census Division, ON; Ontario, Canada TD Full-time €69,700 - €98,400

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Technology Solutions

Pay Details:

$69,700 - $98,400 CAD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate’s skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

Role Summary

As a Software Engineer I, you develop and maintain technical solutions for EDMO Data Catalog services, ensuring adherence to engineering and architectural design principles while meeting business requirements. You build and support defined components within cloud-enabled solutions, applying documented infrastructure, deployment and architecture patterns with guidance from senior engineers. You work on defined features, components, enhancements and break / fix work under the guidance of senior engineers and technical leads.

You contribute to the full delivery lifecycle by analysing requirements, building quality code, performing unit and component testing, supporting peer reviews and participating in production support. You are expected to apply enterprise standards for security, reliability, scalability and maintainability while growing your knowledge of the platform and business domain.

You use AI-assisted engineering tools only within approved guidance, treating generated outputs as drafts that must be tested, reviewed and validated before use.

Key Outcomes

  • Defined features, components and enhancements are delivered on time and aligned to documented requirements and architecture standards.
  • Code is maintainable, tested and consistent with team standards, with defects identified and resolved early in the delivery cycle.
  • Assigned features and components are implemented in alignment with documented cloud, infrastructure, security and scalability patterns.
  • Technical documentation, test evidence and implementation notes are clear enough to support handoff, operations and future maintenance.
  • Incidents, defects and support requests are analysed with appropriate urgency and escalated when risks or blockers emerge.
  • Knowledge of the business domain, platform and engineering practices grows through hands‑on delivery and active participation in the team.

Customer

  • Develop new solutions, features and components for assigned engineering programs and platform initiatives.
  • Develop and test assigned components within approved cloud-enabled architecture and deployment patterns.
  • Perform unit and component testing for new application development aligned to business needs and technology architecture standards.
  • Support business enquiries, small enhancements and break / fix implementations, including source code changes where required.
  • Work with technology partners to ensure configuration and custom components meet application requirements and performance goals.
  • Analyze technical requirements for assigned work and recommend pragmatic engineering solutions with guidance from senior team members.
  • Document and verify system components, applications, system infrastructure, security, integration and operability designs associated with assigned work.

AI Workflow Innovation & Governance

  • Use approved AI-assisted development tools for defined tasks such as code suggestions, test scaffolding, documentation drafts and refactoring support.
  • Validate generated outputs through unit tests, peer review, secure coding checks and comparison against requirements before relying on them.
  • Never use sensitive or restricted information in AI prompts unless explicitly approved by policy and project guidance.
  • Capture useful exa