Work Location:
Toronto, Ontario, Canada

Hours:
37.5

Line of Business:
Technology Solutions

Pay Details:

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:

Department Overview:

Branch & Infrastructure Technology Solutions in Servicing & Digital Enablement Platform is a critical part of the bank providing technology solutions for Canadian Personal Banking. You will be part of Quality Engineering team focusing on delivering high quality Software for our Colleagues and Customer facing applications.

Job Details - What you'll do:

* You will Own end-to-end (E2E) quality and delivery for large, complex systems - defining the E2E test artifacts, automation, governance, environments, and quality gates that ensure release readiness.

* Lead automation-first validation of critical business functionalities across API, UI, data, and integration layers, and provide clear, consistent quality signals to senior stakeholders.

* Define and own the E2E QE strategy for all Malcodes owned by your pod: scope, test architecture (test pyramid and E2E layers), quality gates, environments, test data, and entry/exit criteria for releases.

* Drive E2E automation across critical user applications and integrations (API/UI/data/message flows), ensuring scalable coverage, maintainability, and low-flake execution suitable for CI/CD.

* Coordinate cross-functional and cross-team delivery: align pods, platform teams, vendors, and external dependency teams on E2E schedules, readiness, and environment stability.

* Partner with Product Owners, Engineering Leads, Architects, and Operations to translate business priorities, NFRs, and architectural changes into risk-based E2E test plans and measurable outcomes.

* Establish governance and reporting for E2E quality: dashboards for coverage, pass rates, flakiness, defect leakage, and release readiness; communicate status and risks to QE leadership.

* Lead integrated defect triage and root-cause analysis across systems using logs, traces, and telemetry, drive remediation and regression prevention through automated checks and improved observability.

* Own E2E test execution planning and delivery for major releases: coordinate dry runs, manage change windows, orchestrate parallel execution, and ensure timely go/no-go recommendations.

* Improve QE processes at scale: standardize frameworks and patterns, introduce service virtualization/mocking where needed, and optimize cycle time through CI/CD integration and environment strategy.

* Act as the primary QE point of contact for stakeholders to facilitate decision-making, resolve blockers, manage expectations, and ensure transparent communication.

* Implement AI solutions to QE Workflow in SDLC.

Where you'll work:

* After completing in-person training and onboarding sessions, you'll work primarily onsite in Toronto.

* Your remaining time will be spent at a TD location for in-person team events and experiences. The hiring manager will provide more information about how this works for their team.

Job Requirements - What you'll need to succeed:

* Own automation QE delivery for a pod: define automation scope, API/UI coverage, and entry/exit criteria; drive execution to meet sprint and release commitments.

* Partner with Product Owners, Engineers, and stakeholders to translate user stories, NFRs, and architecture into risk-based test strategy and clear, trackable deliverables.

* Partner with the QE from multiple teams during end-to-end integration testing: contribute pod-level test scenarios, execute validation (automation and targeted manual), and support integrated release readiness across dependent systems.

* Leverage architecture diagrams, data flows, and logical data models to build efficient automated test design (API/contract tests, component tests, and UI automation) with maintainable abstractions.

* Build and extend reusable automation frameworks, libraries, and test utilities aligned with QE standards; drive adoption across the pod and contribute back to the automation practice.

* Lead defect triage and root-cause analysis using logs, traces, and test telemetry; partner with engineering to remediate issues and prevent regressions via automated checks.

* Drive QE execution autonomously on complex initiatives, escalating risks early and aligning stakeholders on mitigation plans, quality gates, and release readiness.

* Coordinate with other pods on shared dependencies (services, environments, test data) and provide pod readiness inputs for integrated releases and E2E test cycles.

* Champion modern test approaches (e.g., BDD where applicable, contract testing, service virtualization, data-driven testing) and work with the Automation Practice Lead to scale patterns and governance.

* Continuously improve QE processes and strategy: define quality metrics (coverage, flakiness, defect leakage), streamline test cycles, and introduce automation and CI/CD quality gates.

* Lead and mentor QE engineers within the pod; drive quality discussions in ceremonies (refinement, planning, demos, retrospectives) and ensure shared accountability for quality.

* Integrate automated tests into CI/CD pipelines; manage test execution in build/release workflows and enable fast feedback through parallelization and environment stability improvements.

* Define and evolve test architecture (test pyramid, tooling selection, environment/test data strategy) to support scalable automation and reliable E2E validation.

* Banking domain experience is highly preferred

* Experience implementing AI tools in Quality Engineering is highly preferred.

Required Skills and Experience:

• Primary Skills - Rest Assured, Selenium, Postman, BDD, Java, Spring Boot, SQL, GitHub, Azure, Jira, X-Ray, AI tools

• BS degree in Computer Science or related Engineering discipline; or equivalent practical experience

• 8+ years of relevant Quality Engineering / SDET experience with strong hands-on automation delivery

• Strong academic background and practical grounding in software engineering fundamentals (testing, CI/CD, and automation best practices)

• Strong expertise with AI tools & models to automate Test Case Creation and Automation script generation in QE workflow.