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About the Role

Join a growing AI platform engineering team and build hands-on skills at the intersection of AI, evaluation, and observability. Contribute to LLM-powered applications and agentic systems that enable teams across the organization to leverage AI capabilities with confidence. Work alongside senior engineers to build and maintain APIs, evaluation frameworks, and monitoring tools that ensure AI systems perform reliably and improve over time.

Responsibilities

• Contribute to the development and maintenance of AI platform components under the guidance of senior engineers.
• Assist in building and maintaining API integrations with LLM providers and internal platform services.
• Help develop LLM-powered applications and AI agents, including prompt engineering, tool integration, conversation management, and orchestration of multi-step workflows.
• Support the enterprise AI API layer by implementing features, fixing defects, and writing tests for internal APIs and SDKs that provide standardized, secure access to AI capabilities.
• Follow established API design standards, versioning policies, and deprecation protocols to ensure platform interfaces remain reliable, developer-friendly, and maintainable.
• Assist with the integration of external AI services, including Anthropic Claude API and other LLM providers, helping ensure connectivity is secure and operationally sound.
• Help build and maintain AI evaluation pipelines, including designing test cases, running model comparisons, and tracking quality metrics to ensure LLM outputs meet accuracy and safety standards.
• Support observability efforts by instrumenting AI services with structured logging, tracing, and dashboards that surface latency, token usage, error rates, and model performance over time.
• Assist in building feedback loops that connect production monitoring signals back to evaluation datasets, helping the team catch regressions and continuously improve AI quality.
• Write clean, well-tested code that adheres to team coding standards, design principles, and documentation expectations.
• Contribute to technical documentation, engineering playbooks, and reference implementations that help development teams adopt common AI patterns.

Requirements

• 0-2 years of software engineering experience, internships, or relevant academic project work in AI/ML, API development, or backend systems.
• Solid foundation in at least one programming language commonly used in AI/ML and platform engineering (Python, Go, Java, or TypeScript).
• Basic understanding of RESTful API design principles, HTTP protocols, and common authentication/authorization patterns (OAuth2, JWT).
• Familiarity with LLM concepts and at least introductory experience using LLM APIs (Anthropic Claude, OpenAI, or similar).
• Interest in building LLM-powered applications or AI agents, with exposure to concepts such as prompt engineering, tool use, and agentic workflows.
• Interest in or exposure to AI evaluation approaches — understanding why measuring model quality, accuracy, and safety matters in production systems.
• Exposure to version control (Git), CI/CD pipelines, and collaborative development workflows.
• Strong willingness to learn, take feedback, and grow in a fast-paced engineering environment.
• Coursework or project experience with vector databases or RAG pipelines (Pinecone, Weaviate, pgvector, Chroma, or equivalent).
• Hands-on experience building LLM-powered apps or agents using frameworks such as LangChain, LlamaIndex, CrewAI, or similar orchestration tools.
• Experience with observability or monitoring tools (OpenTelemetry, or similar) and an interest in applying them to AI systems.
• Awareness of AI security topics such as prompt injection, output filtering, or PII detection.
• Exposure to evaluation frameworks or techniques for LLMs (e.g., RAGAS, DeepEval, custom scoring rubrics, human-in-the-loop review).
• Contributions to open-source projects, personal AI/ML projects, or relevant technical blog posts.

Skills

• AI/ML
• API development
• Backend systems
• Python
• Go
• Java
• TypeScript
• RESTful API design
• HTTP protocols
• OAuth2
• JWT
• LLM APIs
• Prompt engineering
• Tool use
• Agentic workflows
• AI evaluation
• Git
• CI/CD pipelines
• Vector databases
• RAG pipelines
• LangChain
• LlamaIndex
• CrewAI
• Observability
• Monitoring tools
• OpenTelemetry
• AI security
• Prompt injection
• Output filtering
• PII detection
• RAGAS
• DeepEval
• Big Data Management
• Cloud Computing
• Database Development
• Data Mining
• Data Warehousing (DW)
• ETL Processing
• Group Problem Solving
• Quality Management
• Requirements Analysis

Location

• Toronto, Canada

Work Type

• Full time

Experience Level

• Junior
• 0-2 years

About the Company

• RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people.
• The AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations.
• The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery — ensuring RBC remains at the frontier of AI-enabled value creation.
• At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One 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.

Equal Opportunity

• RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.