Mistral AISingapore3h ago
RBCPosted 3w ago
AI Engineer - AI Platform Engineering at RBC scores 83 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Job Description
What is the opportunity?
This role is responsible for designing, building, and hardening platform infrastructure that powers enterprise agentic AI systems and persona-driven workflows to optimize productivity and efficiency. You will work across the full stack of an AI platform, including orchestration, knowledge management, governance, and distribution. The platform enables AI agents to understand user intent, assemble organizational knowledge, and deliver compliant, production-grade process outcomes.
This is a foundational engineering role for anyone passionate about building the infrastructure that makes AI work reliably at enterprise scale in a regulated financial services environment.
What will you do?
- Design and build AI orchestration infrastructure that routes requests, manages multi-stakeholder context, and coordinates multi-step long-running agent workflows across enterprise environments
- Develop knowledge management and retrieval systems that enable AI agents to reason across codebases, documentation, and organizational knowledge sources
- Build and maintain packaging, validation, and deployment pipelines that distribute AI capabilities across development tools and platforms
- Implement governance and compliance frameworks including audit trails, policy enforcement, traceability, and quality scoring for regulated environments
- Design extensible architectures that allow new AI capabilities and integrations to be registered, validated, and activated dynamically
- Ensure platform reliability through edge case handling, graceful failure recovery, and performance optimization behind corporate infrastructure
- Develop conventions, standards, and architectural patterns that maintain consistency as the platform scales across teams
- Collaborate with cross-functional teams to align platform capabilities with the needs of solution architects, analysts, developers, and project managers
What do you need to succeed?
Must Have
- Experience with LLM orchestration, prompt engineering, agentic AI systems, or AI infrastructure
- Familiarity with knowledge management systems, retrieval-augmented generation (RAG), or information retrieval
- Python and/or TypeScript engineering background with experience building production-grade platform infrastructure
- Understanding of enterprise governance, audit trails, and compliance requirements in regulated industries
- Experience with CI/CD pipelines, build systems, and multi-platform distribution
- Ability to design extensible architectures and communicate technical concepts to both technical and non-technical stakeholders
Nice to Have
- Cross-platform development experience and familiarity with IDE extension or plugin ecosystems
- Experience with graph databases, knowledge graphs, or federated data systems
- Background in financial services technology or other regulated industries
- Familiarity with developer experience tooling, internal developer platforms, or software catalogs
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
- Flexible work/life balance options
- Opportunities to do challenging work
Job Skills
Big Data Analytics, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Software Engineering, Software Product DesignAdditional Job Details
Address:
745 THURLOW ST:VANCOUVERCity:
VancouverCountry:
CanadaWork hours/week:
37.5Employment Type:
Full timePlatform:
TECHNOLOGY AND OPERATIONSJob Type:
RegularPay Type:
SalariedPosted Date:
2026-08-11Application Deadline:
2026-11-29Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
Our Employment Opportunities
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.
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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.
RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, Rag, and AI Agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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