Analytics, Insights, & Artificial Intelligence Pay Details: $154,000
- $199,500 CAD This role is temporarily eligible for a pay premium above the posted salary range that is reassessed annually. TD is committed to providing fair and equitable compensation opportunities to all colleagues. 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. We are looking for an AI Platform Product Engineer who can lead AI initiatives from idea to production, and who can teach our engineers to build with AI. This person is technical enough to prototype agents and RAG solutions. The role sits between our platform engineering teams and the business. It owns a portfolio of AI initiatives: it defines them precisely, prioritizes the work, removes blockers and proves value with measurable results. It also builds our engineers' AI skills through hands-on training, live demos and reusable learning materials. We care less about AI credentials and more about demonstrated skill. AI Program Leadership Passionate about Generative AI and Machine Learning AIOps/MLOps mindset enabling services and developing pipelines for managing training models and production models Own the vision, objectives and key results for a portfolio of AI initiatives Build and continuously prioritize the AI product backlog, writing backlog items with explicit acceptance criteria so engineers can commit with confidence Turn vague business requests into precise AI use cases with defined scope, constraints, success metrics and a clear definition of done Run AI work in short iterations: plan, review, accept or reject increments Act as the main liaison between business stakeholders, engineering, security, risk and compliance,



and keep senior leaders informed Identify and track cross-pod dependencies and risks, and keep a prioritized risk backlog Build business cases that show ROI, including the full cost of running AI in production (model usage, tokens, infrastructure and support) AI Enablement for Engineers Design and run a training program that teaches platform engineers and developers to build agents, multi-agent workflows and RAG solutions Run regular demo sessions, workshops and office hours that show new AI techniques applied to our own platforms Teach engineers how to structure context for AI, evaluate AI output, recognize common failure patterns and keep costs under control Build a community of practice: share lessons learned, publish internal guides and grow AI champions in each team Measure the impact of training through skills assessments and adoption, and update the curriculum as the technology changes AI Platform Engineering Build proofs of concept and prototypes for agents, RAG pipelines and multi-agent workflows to test ideas before teams commit Design evaluation suites (test sets, automated evals, regression checks and metrics) for AI features before and after release CI/CD for AI, monitoring, versioning and observability Apply AI security and guardrails, including prompt injection defenses, content filtering, access controls and human approval for high-risk actions Make sure all AI solutions meet internal security, privacy,



regulatory and responsible AI standards for financial services 5+ years in cloud, platform engineering, technical product ownership or technical program management 2+ years of hands-on work with generative AI, including building or shipping LLM applications, agents or RAG solutions Working knowledge of at least one major cloud (Azure, AWS or GCP) and its AI services Practical Python skills and experience with at least one LLM framework (such as LangChain, LlamaIndex or Semantic Kernel) or agent framework Understanding of RAG components: chunking, embeddings, vector databases, retrieval and optimization Experience designing evaluations for AI systems, with an understanding of common failure modes Knowledge of AI security risks, including prompt injection and data leakage, and how to mitigate them Demonstrated backlog management in Agile teams, using tools such as Jira and Confluence Proven ability to influence senior stakeholders across a matrixed organization Experience teaching technical topics, through workshops, demos, internal talks, documentation or mentoring Strong communication skills, with the ability to build clear presentations and explain complex AI ideas simply TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Together, we are reimagining what banking can be for our clients, colleagues and communities. Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs,

📌 AI / ML Product Engineer (Canada)
🏢 The Toronto-Dominion Bank (Canada)
📍 Canada