What is the opportunity?

As an AI Engineer at RBC, you will help build the next generation of autonomous and semi-autonomous AI platform and solutions for Risk & Security. You’ll work alongside experienced engineers to design, develop, and deploy production-grade AI and ML systems, gaining exposure to large language models, machine learning, data engineering, and modern cloud technologies. With access to advanced AI tools and a collaborative environment, you’ll contribute to projects that drive automation, increase operational efficiency, and support regulatory compliance.

What will you do?

• Design, build, and deliver robust AI/ML models and automation solutions in Python or TypeScript to automate key risk, audit, and security workflows.
• Build AI solutions using LLMs and RAG systems (OpenAI, Cohere, Claude, Llama), vector search (pgvector, Milvus, Pinecone), and advanced context engineering pipelines (LangChain, Semantic Kernel) to ensure AI actions are context-aware, secure, and aligned with real-time enterprise data.
• Own the deployment, monitoring and optimization of classical ML models (e.g., XGBoost, Isolation Forest) for anomaly detection, data quality or trend analysis.
• Engineer and maintain scalable data pipelines and workflows using Spark, Databricks, or Airflow, and deliver and maintain APIs (REST, GraphQL, FastAPI, gRPC).
• Integrate AI services with enterprise platforms (e.g., Archer GRC, ServiceNow IRM) and modern infrastructure (AWS, Azure, or on-prem).
• Build, test and document SDK plug-ins and reusable modules for risk, regulatory, and security AI automation.
• Apply and advocated for best practices in secure coding and MLOps CI/CD automation (Docker, Kubernetes, GitHub Actions, Jenkins) and observability (Prometheus, Grafana) Contribute to code reviews, collaborate with data scientists and engineers, front and backend engineers and ML engineers, and maintain clear technical documentation.

What do you need to succeed?

Must Have

• Bachelor’s degree (or equivalent experience) in Computer Science, Software Engineering, or a related field. 2–4 years of software engineering experience with Python and/or TypeScript; familiarity with Java or Go is an asset.

• Hands-on experience deploying ML/AI solutions (LLMs, RAG, classical ML) into Production, including model fine-tuning and vector database use (pgvector, Milvus, Pinecone) and MLOps using PyTorch, TensorFlow, or HuggingFace.

• Strong Experience building data pipelines and APIs with Spark, Databricks, Airflow, SQL (Snowflake, Postgres), and NoSQL (MongoDB); experience with REST, GraphQL or FastAPI. Strong experience with modern MLOps/DevOps: Docker, Kubernetes, CI/CD pipelines (Github Actions, Jenkins, Argo CD), and Cloud/On-prem platforms (AWS, Azure, on-prem GPU etc..)

• Ability to independently deliver complex features and prototypes within aggressive timelines and contribute to team best practices.

Nice to Have

• Experience working with LLMs, RAG frameworks (LangChain, Semantic Kernel), or vector databases (pgvector, Milvus, Pinecone), LLM fine-turning (LoRA, PEFT), prompt-engineering, and large-scale model deployment (HuggingFace, DeepSpeed, ONNX).

• Familiarity with cloud environments (AWS, Azure, or GCP) and integrating APIs or enterprise systems (e.g., Archer GRC, ServiceNow IRM). Understanding of MLOps concepts (Kubernetes, Argo CD), monitoring tools (Prometheus, Grafana), or secure coding practices (SAST/DAST).

• Awareness of IT risk, security, or regulatory frameworks (NIST, ISO, SOX/ITGC).

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable

• Leaders who support your development through coaching and managing opportunities

• Ability to make a difference and lasting impact

• Work in a dynamic, collaborative, progressive, and high-performing team

• A world-class training program in financial services

• Opportunities to do challenging work

• Opportunities to take on progressively greater accountabilities

• Opportunities to building close relationships with clients

• Access to a variety of job opportunities across business and geographies.

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Job Skills

AI Systems, Application Engineering, Artificial Intelligence (AI), Big Data Analytics, Client Counseling, Critical Thinking, Data Engineering, Data Pipelines, Decision Making, Engineering Development, Generative AI, Industry Knowledge, Information Retrieval, Large Language Model (LLM) Fine-Tuning, Machine Learning, Model Building, Prompt Engineering, Software Development, Software Engineering, Software Product Design

Additional Job Details

16 YORK ST:TORONTOTORONTOCanada37.5Full timeTECHNOLOGY AND OPERATIONSRegularSalaried2025-07-082025-07-31

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Inclusion and Equal Opportunity Employment

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.