We are looking for a Full Stack Engineer who can design and deliver scalable, enterprise-grade solutions while building AI capabilities directly into our platforms. We are looking for a Full Stack Engineer who can design and deliver scalable, enterprise-grade solutions while building AI capabilities directly into our platforms. Has hands‑on experience building with large language models and can apply them responsibly in a regulated environment You will work across frontend, backend, and integration layers to build reliable systems, while delivering AI-enabled capabilities where they create genuine business value.

Candidates are not expected to have a research background in machine learning. There will be opportunity to develop deeper expertise in areas such as agentic systems, orchestration, and model evaluation, supported by structured learning and meaningful project work. Develop user-facing applications with a strong focus 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 (RAG) capabilities that make internal policy, product, and client information accessible and actionable Design, build, and support end-to-end applications across frontend, backend, and integration layers Translate business requirements into scalable technical solutions Build robust microservices and APIs using Java, Node.js, or Python Develop intuitive frontend applications using React or Angular Identify opportunities to leverage AI development tools to improve delivery efficiency Contribute to continuous improvement of engineering practices covering quality, CI/CD, and observability Implement and optimize RAG pipelines covering chunking strategy, embeddings, vector search,



and grounding of responses in source documents Establish validation and evaluation practices to assess AI output quality and identify regressions before release Apply appropriate safety and security controls including input validation, PII handling, prompt injection mitigation, and human‑in‑the‑loop review for material decisions Core Technical Stack Java (Spring Boot), Node.js, Python Frontend: Angular or React AI / LLM: LangChain, AWS Bedrock, Azure OpenAI, Copilot Studio, OpenAI and Anthropic APIs Vector databases including pgvector, OpenSearch or Pinecone, or Chroma Data: SQL/NoSQL, Oracle Infrastructure: AWS/Azure, Docker, Kubernetes, Kafka Tools: CI/CD pipelines, observability platforms Candidates are not expected to have experience across the full stack listed.

Proficiency in at least one backend language (Java, Node.js, or Python) and one frontend framework (React or Angular) ~ Solid understanding of system design, API development, and building for scale ~ Strong communication and collaboration skills, including the ability to engage non‑technical stakeholders ~ Hands‑on experience building applications with large language models, with the ability to discuss design decisions, challenges encountered, and lessons learned ~ Practical understanding of prompt engineering and methods for evaluating output quality ~ Familiarity with RAG concepts including embeddings, vector search, and the relationship between retrieval quality and output quality ~ Exposure to agentic AI, 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 ~ Experience using AI development tools such as Copilot and code assistants within a team setting ~ Production experience supporting an LLM‑based feature serving end users Awareness of AI security considerations including prompt injection, data leakage, and output validation, with reference to the OWASP LLM Top 10 Familiarity with search, data retrieval, or analytics platforms Applies considered judgement to AI, distinguishing between promising capability and production readiness Risk‑aware, recognizing that probabilistic outputs require appropriate controls in a banking context Continuously learning, including how AI can enhance both products and engineering productivity Salaries for part‑time roles will be pro‑rated based on number of hours regularly worked. BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance‑based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans.

It calls on us to create lasting, positive change for our customers, our communities and our people. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs.

From in-depth training and coaching, to manager support and network‑building opportunities, we’ll help you gain valuable experience, and broaden your skillset. Accommodations are available on request for candidates taking part in all aspects of the selection process. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

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📌 Full Stack Engineer (AI-Enabled) (Calgary)
🏢 BMO
📍 Calgary