Which banks are hiring for AI in Toronto? 22 open roles at 3 banks.

Which banks have the most AI openings in Toronto?

Data as of Oct 1, 2026 – Oct 25, 2026 · 3 banks · 22 postings · each bank's own careers site. A job posting is evidence that a bank is recruiting, not of what it has deployed; for that, read the bank's page. Counts are AI-titled postings listed on the profile, not headcount, and a profile lists at most 12 postings per bank. 1 of the 100 snapshots are older than 21 days and are marked stale below.

What AI titles are banks posting in Toronto?

Data as of Oct 1, 2026 – Oct 25, 2026. Each title links to the posting on the bank's careers site; postings close without notice.

Which kinds of AI roles are open in Toronto?

Data as of Oct 1, 2026 – Oct 25, 2026. Families overlap. Family pages: Responsible AI & governance · AI security · AI research · Agentic AI & LLM · ML & data science · AI product & strategy · AI engineering.

Where else are banks hiring for AI?

How are these counts built, and what do they not show?

Each bank page on this site carries an “Open AI roles” block: the postings whose title names AI, machine learning, data science, generative AI, LLMs, agents or MLOps on the bank's own careers site on the date shown, found by searching that site and keeping only titles that are about AI. 100 of the 141 bank pages carry such a block as of Oct 1, 2026 – Oct 25, 2026; the other 41 have not been surveyed yet, or their careers sites could not be searched, so a bank missing here is not a bank that is not hiring. A profile lists at most 12 postings, so a count of 12 means “at least 12” and is shown as 12+.

Role families are assigned from the title alone with fixed word lists (responsible AI & governance: titles naming responsible AI, AI governance, AI risk, model risk, AI compliance, supervision, controls, validation or ethics; AI security: titles naming security, cyber, identity, threat, red team, offensive security, DLP or data protection alongside AI; AI research: titles naming AI research, research scientists or fellows, and applied machine-learning scientists; agentic AI & LLM: titles naming agents, agentic AI, LLMs, generative AI, RAG, prompt or context engineering, conversational AI, copilots or chatbots; ML & data science: titles naming data science, machine learning, ML, MLOps, modelling, quantitative analytics, data engineering or data architecture alongside AI; AI product & strategy: titles naming product, programme, strategy, transformation, enablement, adoption, go-to-market, consulting, analysis or AI leadership (head of AI), plus AI internships; AI engineering: titles naming engineers, architects, developers, SREs, DevOps, platforms, infrastructure, cloud, integration or automation alongside AI); a title can sit in more than one family, so family counts add up to more than the number of postings. Seniority is also read from the title: VP, SVP, director, executive director, managing director and “head of” count as leadership (at US banks a vice president is often a mid-level grade); principal, lead, staff, distinguished and manager titles are the middle band; everything else, interns included, is the third. Locations are the first city a posting names; postings that name only a country, “2 locations” or nothing are left out of the city tables.

Postings are a snapshot: they close, reopen and get re-titled, and the same requisition can appear in several cities. Counts are not headcount, not budgets and not a measure of how far a bank's AI programme has gone; a bank that hires through agencies, internal transfers or untitled “software engineer” requisitions will look smaller here than it is. Where a posting carries no date, the careers site did not show one. Snapshots older than 21 days are flagged as stale; each bank's page shows the same list with its own date, and the AI index is the place for what banks have actually put on the record.