Staff AI Engineer: Agentic AI & Production Systems

RBC; Toronto; On-site; CAD 170,000 - 210,000; Full time

Job summary

RBC is seeking a Staff Engineer to drive development of agentic AI systems within Global Functions Technology. You will design MCP servers, RAG pipelines, and multi-agent workflows, collaborating across teams to deliver scalable, production-ready AI capabilities for the enterprise.

You will steer architectural decisions, mentor engineers, and ensure robust security and governance while leveraging MCP, A2A, and cutting-edge AI tooling at RBC.

Qualifications

• 5-8 years building production software systems at scale.
• 1-3 years working hands-on with LLMs and generative AI in production.
• Solid experience with agentic AI patterns — tool use, agent orchestration, ReAct, multi-step reasoning, memory and context management.
• Strong Python skills and a commitment to writing clean, maintainable, production-grade code.
• Experience building RAG systems with vector databases, embeddings, and retrieval strategies.
• Working knowledge of MCP or similar agent-tool integration frameworks.
• Comfort with cloud platforms (AWS, Azure, or GCP), containers (Docker/Kubernetes), and CI/CD.
• Proven ability to lead technically — driving cross-team decisions, reviewing architecture, mentoring engineers.
• Clear communicator who can explain complex AI trade-offs to both technical and business audiences.
• Understanding of security, data governance, and responsible AI practices.

Responsibilities

• Build agentic AI systems end-to-end — design and implement agent orchestration, MCP servers, RAG pipelines, and multi-agent workflows that run reliably in production.
• Set technical direction — make architecture decisions on how agents interact with tools, manage context, route between models, and recover from failures.
• Ship production AI — write clean, well-tested Python code for systems that real users and business teams depend on every day.
• Drive quality and safety — build evaluation frameworks, prompt versioning, guardrails, and observability so agent behavior stays reliable across model updates.
• Enable other teams — create reusable components, run enablement sessions, and mentor engineers on agentic AI patterns and best practices.
• Stay at the frontier — evaluate emerging models, frameworks, and protocols (MCP, A2A) and bring the best ideas back to the team.

Skills

Agentic AI patterns

Python

LLMs in production

Architecture decisions

Cross-team leadership

Tool integration

Security and governance

MCP framework knowledge

Cloud platforms (AWS/Azure/GCP)

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

CrewAI

Weigths & Biases

Job description

RBC is seeking a Staff Engineer to drive development of agentic AI systems within Global Functions Technology. You will design MCP servers, RAG pipelines, and multi-agent workflows, collaborating across teams to deliver scalable, production-ready AI capabilities for the enterprise.

You will steer architectural decisions, mentor engineers, and ensure robust security and governance while leveraging MCP, A2A, and cutting-edge AI tooling at RBC.