Software Engineer II- Salesforce

Work Location: Toronto, Ontario, Canada

Hours 37.5

Line Of Business Technology Solutions

Pay Details $81,600 - $115,200 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 Department Overview Join a team delivering enterprise-grade Salesforce solutions in a highly regulated, high-visibility environment where platform stability, secure design, traceability, and strong engineering discipline matter. This role supports critical business workflows and contributes to solutions that must balance speed, scale, governance, and long-term architectural integrity. The work includes scalable Salesforce development, integration patterns, and AI-enabled capabilities that require strong human-in-the-loop controls, clear trade-off analysis, and disciplined execution.

What You’ll Do As a Software Engineer II with a strong Salesforce development profile, you will design, build, and support secure, scalable, and maintainable Salesforce solutions that operate in a critical enterprise environment. You will partner closely with product, architecture, risk, and delivery teams to develop solutions that are technically strong, operationally resilient, and aligned to governance expectations. This role is best suited for a hands-on engineer who combines deep Salesforce technical skills with strong judgment, ownership, and the ability to work through ambiguity in high-impact initiatives.

What You’ll Do Day To Day

• Design and build robust Salesforce solutions using Apex, Lightning Web Components, flows, integrations, and secure data access patterns for enterprise-scale use cases.
• Translate complex business requirements into clean technical designs, with strong attention to scalability, reusability, performance, and supportability.
• Work on solutions where reliability, auditability, and controlled data access are essential, including capabilities that interact with sensitive business workflows and governed data boundaries.
• Collaborate with architects, product partners, and cross-functional teams to document options, trade-offs, sequencing, and implementation approaches before development begins.
• Contribute to a future-ready engineering foundation so new use cases, models, and capabilities can be onboarded without re-engineering the entire solution.
• Support development through design, build, testing, deployment, and production stabilization, with a strong focus on quality engineering and operational readiness.
• Troubleshoot complex platform, integration, and data issues in partnership with delivery and support teams.
• Uphold strong engineering standards across code quality, documentation, DevOps discipline, risk controls, and secure SDLC practices.

AI Adoptability & Modern Engineering Expectations We are looking for a candidate who can help the team adopt AI responsibly and practically within Salesforce engineering workflows. In this role, AI adoptability means using approved enterprise AI capabilities to improve developer productivity, design quality, summarization, classification, knowledge retrieval, and future workflow enablement—while respecting governance, access control, validation, and human review requirements.

Strong Candidates Should Be Able To

• Evaluate where AI can accelerate engineering work without compromising quality, compliance, or architectural integrity.
• Design Salesforce solutions that are model agnostic where possible, so future AI capabilities can be introduced in a scalable and reusable way.
• Work effectively with enterprise-approved model options such as GPT-based models and embeddings available through TD AI Platform environments, including examples like gpt-5, gpt-5-mini, gpt-4.1, gpt-4.1-mini, text-embedding-3-large, and model-router, d…