Job DescriptionWhat is the Opportunity?As a
Senior AI Engineer on the
ASEDA team, you'll be building the agentic AI and generative AI systems that are transforming how the enterprise operates. Think AI agents that can reason, plan, use tools, and take action across real business workflows - not chatbot demos, but production systems that move the needle.
You'll build MCP servers, agent orchestration pipelines, and RAG systems that connect large language models to the enterprise. You'll own complex features end-to-end, collaborate closely with Staff and Principal Engineers on architecture, and raise the quality bar for the team. This is a role where your code ships, your technical depth matters, and you'll grow rapidly in one of the most exciting areas in software.
We value positive attitude, willingness to learn, open communication, teamwork, and commitment to clean, secure and well-tested code.
What will you do? - Build agentic AI systems - design and implement agent orchestration, MCP servers, RAG pipelines, and multi-agent workflows that run reliably in production
- Own complex features end-to-end - take ambiguous requirements and deliver well-architected, well-tested solutions from design through deployment
- 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 - contribute to evaluation frameworks, prompt versioning, guardrails, and observability so agent behavior stays reliable across model updates
- Collaborate and learn - work closely with Staff and Principal Engineers on architecture decisions, participate in code reviews, and share knowledge with the team
- Stay at the frontier - explore emerging models, frameworks, and protocols (MCP, A2A) and bring the best ideas back to the team
What do you need to succeed? Must-Have- 4-6 years building production software systems - you know what it takes to ship and operate reliable code at scale
- 1-2 years working hands-on with LLMs and generative AI in production or serious prototyping
- Working knowledge of 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 or contributing to RAG systems with vector databases, embeddings, and retrieval strategies
- Familiarity with MCP or similar agent-tool integration frameworks
- Comfort with cloud platforms (AWS, Azure, or GCP), containers (Docker/Kubernetes), and CI/CD
- Strong collaboration skills - you thrive in code reviews, design discussions, and pair programming
- Clear communicator who can explain technical decisions to both peers and business stakeholders
- Understanding of security, data governance, and responsible AI practices
Nice-to-Have- Experience with agent frameworks (LangChain, LangGraph, LlamaIndex, Semantic Kernel, CrewAI)
- Hands-on with AI observability tooling (LangSmith, LangFuse, Weights & Biases)
- Familiarity with multi-agent protocols (A2A) and the broader MCP ecosystem
- Background in NLP, information retrieval, or knowledge graphs
- Experience with prompt/context engineering - versioning, evaluation, and reproducibility
What's in it for you?- Work on what matters - agentic AI, MCP, and multi-agent systems are the most exciting frontier in software right now, and you'll be building it for one of the largest enterprises in the country
- Real impact, real visibility - your work will directly power AI capabilities in RBC
- Access to serious resources - leading foundation models, rich enterprise datasets, and significant compute
- Accelerate your growth - work alongside Staff and Principal Engineers, build deep expertise in agentic AI, and grow into technical leadership
- A team that builds - collaborative, fast-moving, and deeply technical - we ship production AI, not slide decks
- Competitive total rewards - compensation, performance bonuses, flexible benefits, and stock options where applicable
Job SkillsAgentic AI, Artificial Intelligence Technologies, Big Data Management, Data Modeling, Data Science, Decision Making, Deep Learning, Generative AI, LangGraph, Logical Data Modeling, Machine Learning (ML), Model Context Protocol, Predictive Analytics, Programming Languages, Relationship Building
Additional Job DetailsAddress:RBC CENTRE, 155 WELLINGTON ST W:TORONTO
City:Toronto
Country:Canada
Work hours/week:37.5
Employment Type:Full time
Platform:TECHNOLOGY AND OPERATIONS
Job Type:Regular
Pay Type:Salaried
Posted Date:2026-08-04
Application Deadline:2026-08-24
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
