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Bank of Montreal

Runs Canadian and US banks for people and firms

Developer Lead - AI-Enabled Systems

AI Application Engineering +1Updated on Nov 5
Full-timeToronto, ON, Canada$70k - $150kIn-person

About the Job

Requirements

  • At least 7 years of experience in backend or full-stack development.
  • Proficiency in at least one backend language (Java, Node.js, or Python) and one frontend framework (React or Angular).
  • Strong understanding of system design, API development, and building for scale.
  • Experience delivering production-grade applications end-to-end.
  • Strong problem-solving and analytical skills.
  • Demonstrated ownership and accountability for delivery.
  • Ability to work across technology stacks and adapt quickly.
  • Strong communication and collaboration skills, including the ability to engage non-technical stakeholders.
  • Hands-on experience building applications with large language models, including the ability to discuss design decisions, challenges, and lessons learned.
  • Practical understanding of prompt engineering and methods for evaluating output quality.
  • Familiarity with retrieval-augmented generation concepts, including embeddings, vector search, and the relationship between retrieval quality and output quality.

Responsibilities

  • Build and enhance core banking and client onboarding platforms.
  • Design APIs and backend services supporting complex, multi-step workflows.
  • Develop user-facing applications focused on usability and performance.
  • Work on data-driven systems, integrations, and orchestration layers.
  • Deliver AI-assisted capabilities including document processing, intelligent onboarding workflows, search and summarization, and decision support.
  • Implement retrieval-augmented generation capabilities that make internal policy, product, and client information accessible and actionable.
  • Contribute to modernization initiatives including API-first design, cloud adoption, and event-driven architecture.
  • Design, build, and support end-to-end applications across frontend, backend, and integration layers.
  • Translate business requirements into scalable technical solutions.
  • Own features from design through production and support.
  • Collaborate with product, architecture, and business teams to solve complex domain problems.
  • Build robust microservices and APIs using Java, Node.js, or Python.
  • Develop intuitive frontend applications using React or Angular.
  • Ensure systems are secure, resilient, and compliant with banking requirements.
  • Identify opportunities to use AI development tools to improve delivery efficiency.
  • Contribute to continuous improvement of engineering practices covering quality, continuous integration and continuous delivery, and observability.
  • Develop features using large language model APIs, including prompt design, structured output handling, tool calling, and management of errors and edge cases.
  • Implement and optimize retrieval-augmented generation pipelines covering chunking strategy, embeddings, vector search, and grounding responses in source documents.
  • Establish validation and evaluation practices to assess AI output quality and identify regressions before release.
  • Apply safety and security controls, including input validation, personally identifiable information handling, prompt injection mitigation, and human-in-the-loop review for material decisions.
  • Manage cost and latency considerations associated with model usage.

Desired Qualifications

  • Experience in banking or financial services, particularly onboarding, payments, lending, trade, or know-your-customer/anti-money-laundering; candidates from other regulated or complex domains will also be considered.
  • Production experience supporting a large-language-model-based feature serving end users.
  • Exposure to agentic artificial intelligence, including agents capable of planning and tool use, multi-agent workflows, and human-in-the-loop approval patterns.
  • Experience with LangChain or LangGraph, AWS Bedrock, or Copilot Studio.
  • Awareness of AI security considerations including prompt injection, data leakage, and output validation, with reference to the OWASP Large Language Model Top 10.
  • Experience with model evaluation frameworks or large language model observability tooling.
  • Familiarity with search, data retrieval, or analytics platforms.
  • Experience with cloud-native or modernization programs.
  • Understanding of event-driven or streaming architectures.
  • Experience using AI development tools such as Copilot and code assistants within a team setting.

About the Company

Bank of Montreal

Runs Canadian and US banks for people and firms

Bank of Montreal, known as BMO, runs a Canadian bank and a large American bank, serving households and businesses on both sides of the border. Until the Bank of Canada opened in 1935, it acted as the Canadian government's banker. People use its branches and apps for accounts, mortgages, credit cards, and investments, while companies borrow from it and turn to its BMO Capital Markets arm to raise money and trade securities. BMO makes money on the gap between the interest it charges on loans and pays on deposits, plus fees from managing wealth and advising on deals. Bank of Montreal was founded in 1817 as Canada's first bank, and it keeps its legal head office in Montreal and its executive offices in Toronto, Canada.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1817

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