AI Engineer I

About the Role We are seeking an AI Engineer I to design, develop, and deploy applied AI and agentic AI solutions that power decision intelligence, automation, and performance optimization across the enterprise. You will collaborate with data scientists, AI engineers, and product teams to translate ideas into scalable production systems that deliver measurable business value. Key Responsibilities Design and implement machine learning and agentic AI systems leveraging LLMs, RAG pipelines, and multi-agent frameworks (e.g., LangChain, Hugging Face). Build and maintain data ingestion and feature pipelines using PySpark, Databricks, and SQL for model training and inference. Deploy, monitor, and optimize AI microservices on Azure or Databricks clusters, ensuring robustness, security, and scalability. Develop reusable components for prompt engineering, vector databases, and conversational agents. Collaborate with MLOps teams to integrate CI/CD pipelines for model deployment and lifecycle management. Contribute to internal frameworks that support governance, traceability, and responsible AI practices. Document technical artifacts, performance metrics, and experiment outcomes; present findings to technical and business stakeholders. Stay current with emerging AI/agentic AI research and identify practical opportunities for adoption. Qualifications Master's or PhD in Computer Science, Engineering, Applied Mathematics, or related field. 3-5 years of hands‑on experience in AI or ML engineering, ideally with exposure to generative AI and LLMs. Proficiency in Python and ML frameworks such as PyTorch or TensorFlow. Familiarity with vector databases (Pinecone, Milvus), RAG architecture, and LangChain or similar agent frameworks. Experience building data pipelines using PySpark and SQL; comfortable working in Databricks or Azure environments. Strong understanding of software engineering fundamentals (Git, Docker, API development, unit testing). Excellent analytical and communication skills, with the ability to translate technical results into business impact. Preferred Experience operationalizing AI models in production environments. Exposure to fraud, authentication, or risk analytics domains. Knowledge of AI governance and responsible AI frameworks. Who We Are TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. ... Our Total Rewards Package 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, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Additional Information We're delighted that you're considering building a career with TD. ... Colleague Development If you're interested in a specific career path or are looking to build certain skills, we want to help you succeed. ... Training & Onboarding We will provide training and onboarding sessions to ensure that you've got everything you need to succeed in your new role. Interview Process We'll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call. Accommodation Your accessibility is important to us. Please let us know if you'd like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process. Language Requirement (Quebec only) Sans Objet #J-18808-Ljbffr