Lead, Full Stack Engineer
Role Overview
Hands-on leadership role in AI Engineering within US Functions Technology, covering Finance, Risk, Law, and Audit.
Own modernization solutions from concept to production and help bring CNB US Functions technology into RBC’s enterprise ecosystem.
Work across data, APIs, web services, SSO, security, and messaging integrations.
Key Skills for This Role
Full Job Posting
Role overview
Hands-on leadership role in AI Engineering within US Functions Technology, covering Finance, Risk, Law, and Audit.
Own modernization solutions from concept to production and help bring CNB US Functions technology into RBC’s enterprise ecosystem.
Work across data, APIs, web services, SSO, security, and messaging integrations.
Responsibilities
- Apply AI and agentic tools to business problems across corporate functions.
- Migrate on-premises .NET applications to Azure and design secure, scalable hybrid solutions.
- Plan and deliver application integrations from conception through production deployment.
- Lead API, web service, SSO, security, and Kafka or MQ architecture and integration.
- Build backend APIs and web services and coordinate CNB entity integration and business adoption.
- Consolidate CNB Finance and Audit applications onto the RBC common platform.
- Develop Python scripts and data pipelines.
- Lead, mentor, and grow engineers and set technical direction and quality standards.
- Use Splunk, Elastic, and performance monitoring to support enterprise operations.
- Gather stakeholder requirements and align AI initiatives with business strategy.
- Deploy cloud-native AI/ML solutions on AWS, Azure, or GCP using Kubernetes, Docker, or similar tools.
Qualifications
- At least 7 years leading an engineering team while remaining hands-on.
- Software engineering experience with at least one of .NET, Java, or Python.
- Experience with API and web service integration across SSO, security, and Kafka or MQ messaging.
- Experience migrating applications from on-premises to cloud and running hybrid solutions.
- Ability to turn business requirements into technical roadmaps and identify strategic AI opportunities.
- Experience with ETL, data orchestration, Python scripting, or data pipelines.
- Experience deploying cloud-native solutions with Kubernetes and Docker, and exposure to production AI/ML.
- Experience delivering integration plans to timelines and managing architecture changes.
- Ability to work with enterprise and business stakeholders and align technical delivery with strategic goals.
Preferred experience
- Experience scaling and deploying cloud AI applications, optimizing models, reducing latency, or monitoring performance.
- Experience with RAG systems and vector databases.
- Prompt engineering and AI-based SDLC tools such as Claude or GitHub Copilot.
- Familiarity with LangChain, AutoGen, CrewAI, AI agent architectures, and multi-agent frameworks.
Benefits and work environment
- The posting describes a total rewards program with bonuses, flexible benefits, compensation, and stock where applicable.
- RBC describes a collaborative, high-performing team and opportunities for development and challenging work.
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