Lead, Full Stack Engineer
Role Overview
Hands-on Lead, Full Stack Engineer in AI Engineering, US Functions Technology, supporting Finance, Risk, Law, and Audit.
Leads modernization of .NET applications, adoption of AI and agentic tools, and integration of CNB technology into the RBC enterprise ecosystem.
Owns modernization solutions from concept through production and leads an engineering team.
Key Skills for This Role
Full Job Posting
Opportunity
Hands-on Lead, Full Stack Engineer in AI Engineering, US Functions Technology, supporting Finance, Risk, Law, and Audit.
Leads modernization of .NET applications, adoption of AI and agentic tools, and integration of CNB technology into the RBC enterprise ecosystem.
Owns modernization solutions from concept through production and leads an engineering team.
Responsibilities
- Apply AI and agentic tools to business problems across US corporate functions.
- Migrate .NET applications from on-premises systems to Azure and design secure, reliable, scalable hybrid solutions.
- Develop and manage application integration plans from concept through production deployment, meeting committed timelines.
- Design API, web service, SSO, security, and Kafka or MQ messaging solutions with attention to performance, security, and compliance.
- Build and maintain back-end APIs and web services and deliver SSO, security, and messaging integrations.
- Lead CNB entity integrations with Target Tech teams and support business adoption.
- Consolidate CNB Finance and Audit Tech applications onto the Target RBC Common Platform with business stakeholders.
- Develop Python scripts and data pipelines; lead, mentor, and grow engineers and set technical direction and quality standards.
- Maintain awareness of shared services, Splunk, Elastic, and performance monitoring; gather stakeholder requirements and align AI initiatives to strategic goals.
- Deploy cloud-native AI/ML solutions on AWS, Azure, or GCP using technologies such as Kubernetes and Docker.
Requirements
- At least 7 years leading an engineering team while remaining hands-on and unblocking delivery.
- 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, with architecture decisions addressing performance, security, and compliance.
- Experience migrating on-premises applications to Azure, AWS, or GCP and designing hybrid solutions.
- Ability to translate business requirements into technical roadmaps and identify strategically aligned AI transformation opportunities.
- Strong data skills, including ETL, data orchestration, Python scripting, or pipeline development.
- Experience deploying cloud-native solutions with Kubernetes and Docker, with exposure to production AI or ML.
- Experience delivering integration plans to deadlines, managing architecture changes, and collaborating with enterprise and business stakeholders.
Additional qualifications
- Experience scaling cloud AI applications, optimizing models, reducing latency, and monitoring performance is a plus.
- Experience with RAG systems and vector databases is a plus.
- Prompt engineering, AI-based SDLC tools such as Claude or GitHub Copilot, AI frameworks such as LangChain, AutoGen, or CrewAI, and agent architectures are listed as nice to have.
Benefits
- The posting describes a total rewards program with bonuses, flexible benefits, compensation, commissions, and stock where applicable.
- RBC mentions coaching and development, challenging work, collaboration, and opportunities to make an impact.
Role context
The engineering work supports Finance, Risk, Law, and Audit functions and integration with the RBC enterprise ecosystem.
The position is listed as full time, salaried, with 37.5 work hours per week.
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