Lead, Full Stack Engineer

Role overview

What you will do

• Apply AI and agentic tools to problems across US corporate functions.
• Migrate on-premises .NET applications to Azure and design reliable, secure, scalable hybrid solutions.
• Develop and manage application integration plans from conception through production deployment, meeting committed timelines.
• Drive architecture for APIs, web services, SSO, security, and Kafka or MQ messaging, focusing on performance, security, and compliance.
• Build and maintain backend APIs and web services; lead CNB entity integration and support business adoption with Target Tech teams.
• Consolidate CNB Finance and Audit applications onto the target RBC common platform with business stakeholder alignment.
• Perform Python scripting and data pipeline development.
• Lead, mentor, and grow engineers while setting technical direction and quality standards.
• Maintain understanding of shared services, Splunk, Elastic, and performance monitoring.
• Gather stakeholder requirements, refine visions, align AI initiatives with strategic goals, and translate them into actionable strategies.
• Develop and deploy cloud-native AI/ML solutions on AWS, Azure, or GCP using technologies such as Kubernetes and Docker.

Required qualifications

• At least 7 years leading an engineering team while staying hands-on and unblocking delivery when needed.
• Software engineering background with at least one of .NET, Java, or Python.
• Experience building and integrating APIs and web services across SSO, security, and Kafka or MQ messaging; ability to drive architecture decisions for performance, security, and compliance.
• Proven experience migrating applications from on-premises to Azure, AWS, or GCP and designing and running hybrid solutions.
• Ability to translate business requirements into technical roadmaps and identify AI transformation opportunities aligned with enterprise strategy.
• Strong data skills, including ETL, data orchestration, Python scripting, or data pipeline development.
• Experience deploying cloud-native solutions with Kubernetes and Docker, with exposure to AI or ML solutions in production.
• Experience delivering integration plans to committed timelines, including managing architecture changes.
• Ability to partner with business and enterprise stakeholders, gather requirements, and align technical work with strategic goals.

Nice-to-have experience

• Experience scaling and deploying cloud-based AI applications, optimizing models and latency, and monitoring performance is desirable.
• Experience with Retrieval-Augmented Generation systems and vector databases is desirable.
• Prompt engineering and AI-based SDLC tools such as Claude or GitHub Copilot are desirable.
• Familiarity with Python AI frameworks such as LangChain, AutoGen, or CrewAI is desirable.
• Understanding of AI agent architectures, autonomous decision-making systems, and multi-agent collaboration frameworks is desirable.

Benefits

• RBC describes a total rewards program with bonuses, flexible benefits, competitive compensation, commissions, and stock where applicable.
• The posting mentions coaching and development opportunities, collaborative work, training, and challenging assignments.

Employment details

• The posting lists full-time, regular employment and salaried pay.
• The listed work address is 745 Thurlow Street, Vancouver.