AI Engineer (Global Security)

RBC•Toronto, ON

2d•Onsite

About The Position

As an AI Engineer (Global Security), you will contribute to building RBC’s next-generation platform for autonomous and semi-autonomous AI. You will contribute to the engineering lifecycle to create self-directed, context-aware AI agents and workflows that operate with minimal human intervention, leveraging your expertise in large language models (LLMs), generative AI, machine learning, and data pipelines. You’ll work to deliver highly scalable, production-grade AI solutions that automate complex controls, accelerate regulatory readiness, and set new standards for operational excellence and security.

Requirements

Bachelor's degree (or equivalent) in Computer Science, Software Engineering, or a related field
2-5 years of software engineering experience with Python and at least one of Java, TypeScript, or Go
2+ years of hands-on experience with machine learning, data science, or AI (demonstrated ability to learn and apply generative AI approaches)
Hands-on experience deploying LLMs, RAG systems, and agent orchestration frameworks (e.g., LangChain, CrewAI, AutoGen), including vector database configuration and context engineering for AI workflows
Proficient with MLOps/DevOps, containers, Kubernetes, CI/CD pipelines (Docker, GitHub Actions, Jenkins)

Nice To Haves

Experience with threat detection, security analytics, or threat monitoring systems
Strong mathematical foundations in probability, statistics, and optimization for model design, along with familiarity with distributed ML frameworks (Ray, SageMaker) and real-time pipelines (Kafka, Kinesis)
Awareness of regulatory frameworks and IT controls (NIST 800-53, ISO 27001, SOX)

Responsibilities

Develop and deploy enterprise AI solutions using Python to automate threat detection and remediation processes at scale
Evaluate and recommend technical approaches (multi-agent, single-agent, rule-based) based on threat complexity and regulatory requirements, bringing strategic thinking to architecture decisions
Contribute to the development of LLMs and RAG systems including output quality benchmarking and model performance monitoring (OpenAI, Cohere, Claude via RBC's Claude shop), vector search (pgvector, Milvus, Pinecone), and context engineering pipelines to ensure AI threat detection is accurate, secure, and aligned with data
Build and maintain data pipelines and context layers (Spark, Airflow, SQL/NoSQL) to deliver high-quality intelligence for AI-driven threat detection and automation
Integrate AI solutions with enterprise systems and platforms (Docker, GitHub Actions) and production monitoring tools
Follow and apply best practices in AI safety, privacy, regulatory compliance, and autonomous system guardrails, including model monitoring, fallback mechanisms, and secure deployment in regulated environments (NIST 800-53, SOX)
Collaborate with Global Security, Data Science, and cross-functional teams to refine threat detection requirements, share knowledge, and maintain high-quality technical documentation

Benefits

bonuses
flexible benefits
competitive compensation
commissions
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
Flexible work/life balance options
Opportunities to do challenging work
Opportunities to take on progressively greater accountabilities
Access to a variety of job opportunities across business