Lead, Full Stack Engineer
Role Overview
Hands-on leadership position in AI Engineering supporting US Finance, Risk, Law, and Audit functions.
Own modernization solutions from concept through production, including .NET modernization, AI and agentic tools, and integration with RBC enterprise systems.
Work across data, APIs, web services, SSO, security, and Kafka or MQ messaging.
Key Skills for This Role
Full Job Posting
Role overview
Hands-on leadership position in AI Engineering supporting US Finance, Risk, Law, and Audit functions.
Own modernization solutions from concept through production, including .NET modernization, AI and agentic tools, and integration with RBC enterprise systems.
Work across data, APIs, web services, SSO, security, and Kafka or MQ messaging.
Responsibilities
- Migrate .NET applications from on-premises to Azure and design reliable, secure, scalable hybrid solutions.
- Develop application integration plans and deliver them through production deployment.
- Architect APIs, web services, SSO, security, and messaging integrations; build and maintain backend services.
- Lead CNB entity integration and consolidate Finance and Audit applications onto the RBC common platform.
- Develop Python scripts and data pipelines; support cloud-native AI/ML deployment using AWS, Azure, or GCP, Kubernetes, and Docker.
- Lead, mentor, and grow engineers; set technical direction and quality standards.
- Partner with business stakeholders to gather requirements and translate strategic goals into technical and AI initiatives.
- Maintain familiarity with enterprise operations and monitoring tools including Splunk and Elastic.
Required qualifications
- 7+ years leading an engineering team while remaining hands-on.
- Software engineering background in at least one of .NET, Java, or Python.
- Experience building and integrating APIs and web services across SSO, security, and Kafka or MQ messaging.
- Experience migrating on-premises applications to cloud platforms and operating hybrid solutions.
- Experience with ETL, data orchestration, Python scripting, or data pipelines.
- Experience deploying cloud-native solutions using Kubernetes and Docker, with production AI/ML exposure.
- Ability to deliver integration plans on timelines, manage architecture changes, and work with enterprise and business stakeholders.
Preferred experience
- Scaling cloud AI applications, model optimization, latency reduction, and performance monitoring are preferred.
- RAG systems, vector databases, prompt engineering, AI-assisted SDLC, AI frameworks, and agent architectures are preferred.
Benefits and culture
- The posting describes a total rewards program, flexible benefits, development support, and challenging collaborative work.
Workplace
- The posting lists an RBC office address in Vancouver.
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