Applied AI Scientist – Generative AI & Agentic Systems

BMO•Toronto, ON

3d•CA$67,200 - CA$124,200

About The Position

We are seeking a highly motivated Applied AI Scientist who is passionate about Generative AI and modern software engineering. This role offers an exciting opportunity to build enterprise AI solutions while helping shape industry-leading practices for the validation and governance of Generative AI and Agentic AI systems in a highly regulated environment. The successful candidate will join the Model Risk Management group and report to the Director, Generative and Agentic AI Model Validation. This position is well suited for an early-career AI professional or a recent Master's or PhD graduate with strong coding skills, research or project experience, curiosity, and a passion for emerging AI technologies.

Requirements

Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Software Engineering, Data Science, or another STEM discipline.
Strong programming skills in Python with the ability to develop scalable, well-structured applications.
Hands-on experience with Python libraries and frameworks commonly used for AI application development, data processing, API integration, and software engineering (e.g., NumPy, Pandas, Requests, FastAPI, Pydantic, or similar).
Familiarity with modern software development practices, including Git, version control, testing, and code reviews.
Understanding of machine learning fundamentals and experience applying quantitative analysis techniques.
Hands-on experience or academic projects involving Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, or related technologies.
Familiarity with cloud AI platforms, modern AI development frameworks, or enterprise AI tools is an asset.
Ability to learn new technologies quickly and adapt to a rapidly evolving AI landscape.
Strong analytical thinking, curiosity, and problem-solving skills.
Self-motivated with a strong sense of ownership, attention to detail, and a risk and control mindset.
Inquisitive by nature, willing to challenge assumptions, ask thoughtful questions, and continuously improve existing processes.

Nice To Haves

Loves building software and AI applications.
Is excited by the rapid evolution of Generative AI.
Learns new technologies quickly and enjoys experimenting with them.
Is self-motivated and proactive.
Has strong coding skills and enjoys solving complex technical problems.
Thinks critically and approaches problems with curiosity.
Works well in collaborative, multidisciplinary teams.
Is interested in shaping the future of responsible AI adoption in financial services.

Responsibilities

Validate the effectiveness of Generative AI models and Agentic AI systems across multiple dimensions, including conceptual soundness, output quality, agentic workflow, robustness, and alignment with governance and audit requirements.
Research and develop new methodologies for validating emerging Generative AI technologies.
Design and build enterprise AI applications that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and workflow automation to improve business processes.
Develop scalable software solutions, AI tools, and automation capabilities using modern AI frameworks and cloud technologies.
Work closely with business stakeholders to understand problems and translate them into practical AI solutions.
Design, execute, and document quantitative testing and evaluation of AI models and applications.
Maintain organized project documentation, technical specifications, testing evidence, and validation artifacts to support governance and audit readiness.
Continuously evaluate emerging AI technologies and identify opportunities to improve existing solutions and validation approaches.