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Added 8 mins ago
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Software Engineer II (Salesforce Loyalty Management Developer)
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- Full-time
The Software Engineer II (Salesforce Loyalty Management Developer)
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Royal Bank of Canada

Lead AI Engineer

Toronto, ON, M9W 0A4, Canada

Full-time

This date has passed. Check with the employer before applying.

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Job details

Job type: Full-time
Listed closing date: Oct 9, 2026
Posting language: English
Posted: Sep 18, 2026

Original job description

Job Description

Lead AI Engineer

What is the Opportunity?

We are seeking an accomplished Lead AI Engineer to design, develop, and implement AI-driven solutions within our software development lifecycle. You will lead enterprise-scale AI integration initiatives, establish best practices, and advance the technical maturity of our engineering organization. This role actively contributes to improving our Agile, Engineering, and DevOps practices.

This position demands exceptional problem-solving skills, deep AI expertise, and proficiency in modern development technologies (.NET/C#, Java, Python). You will effectively communicate and collaborate with engineering teams, business stakeholders, and senior management across multiple projects and organizational boundaries.

Role Level and Responsibilities

As a Lead AI Engineer, you are an expert professional with deep technical expertise who contributes to organizational objectives through innovative solutions to complex business challenges. Your primary focus is identifying root causes and implementing solutions to critical business problems while assessing and communicating the technological impact on the business.

Key Activities

Evaluate enterprise software packages and AI platforms, recommending solutions to senior management
Lead and mentor colleagues in AI product reviews, pilot projects, and technology adoption
Conduct in-depth analysis of business requirements for large-scale, mission-critical projects
Perform feasibility studies and translate complex requirements into robust technical designs
Drive adoption of AI-driven practices across engineering teams

What You'll Do

AI Engineering & Implementation

Lead the design and development of MCP (Model Context Protocol) servers and tools for seamless AI integration
Design and implement AI-driven automation solutions, including LLM-powered automation, prompt engineering, and conversational AI
Develop ML model integration solutions and AI orchestration workflows with monitoring and evaluation
Integrate UiPath with enterprise AI platforms and APIs
Support implementation of agentic automation and advanced AI use cases

AI/ML Expertise & Governance

Integrate LLM APIs and apply advanced prompt engineering techniques
Design and maintain AI workflow orchestration systems
Implement Intelligent Document Processing and NLP solutions
Develop model evaluation, tuning, and governance frameworks
Design and manage vector databases and RAG (Retrieval-Augmented Generation) systems
Support responsible AI practices and governance models

AI-Driven Software Development Lifecycle (SDLC)

Implement AI spec-driven development practices for your squad
Contribute to AI/ML solutions that enhance code generation, testing, deployment, and monitoring
Integrate AI technologies into existing SDLC workflows and development tooling
Collaborate on governance and responsible AI implementation

Technical Leadership & Collaboration

Lead technology evaluation and assessment for organizational adoption
Collaborate with enterprise architecture, security, and compliance teams on AI integration
Contribute to technical training and knowledge-sharing initiatives across the organization

What You Need to Succeed

Must Have

10+ years of experience building and operating production software systems at scale
2–4 years of hands-on experience with LLMs and generative AI in production environments
Expert proficiency in .NET/C#, Java, Python, SQL, Git, and CI/CD pipelines
Deep knowledge of design patterns (MVC, MVVM), SOA, and architectural concepts; hands-on development experience with Azure Integration Services
Expert-level expertise in API architecture (REST/SOAP)
Advanced working knowledge of agentic AI patterns: tool use, agent orchestration, ReAct, multi-step reasoning, memory and context management
Proven proficiency in LLM API integration, prompt engineering, and RAG systems (vector databases, embeddings, retrieval strategies)
Demonstrated experience designing and building MCP servers and tools with agent-tool integration frameworks
Cloud platform expertise (AWS, Azure, or GCP), including containers (Docker/Kubernetes) and CI/CD pipelines
Strong collaboration and communication skills; comfortable with code reviews, design discussions, and pair programming
Ability to communicate technical decisions clearly to both technical peers and business stakeholders
Understanding of security, data governance, and responsible AI practices

Nice-to-Have

Experience with agentic automation and advanced AI solutions in production
Open-source contributions to automation or AI/ML projects
Microsoft Azure certification (Azure Developer Associate or Azure Solutions Architect Expert)
Experience building and training machine learning models (regression, classification, clustering) using frameworks like Scikit-learn, TensorFlow, or PyTorch

What's In It For You?

We thrive on the challenge to be our best, embrace progressive thinking, and work together to deliver trusted solutions that help our clients and communities prosper. We are committed to supporting each other's growth and creating mutual success.

Comprehensive Total Rewards Program including competitive compensation, bonuses, flexible benefits, commissions, and stock options where applicable
Development-focused leadership committed to your growth through coaching and career opportunities
Opportunity to make a meaningful, lasting impact on enterprise AI adoption
Dynamic, collaborative, and high-performing team environment
World-class training programs in financial services and emerging technologies

#TechPJ

Job Skills

Application Development, Application Integrations, Application Maintenance, Applications Architecture, Detail-Oriented, Enterprise Application Delivery, Group Problem Solving, Programming Languages, Software Development Life Cycle (SDLC), System Applications

Additional Job Details

Address:

180 WELLINGTON ST W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-08-26

Application Deadline:

2026-10-09

Note: 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.

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More about this job

Responsibilities

The Lead AI Engineer will design and implement enterprise-scale AI solutions, including LLM-powered automation and orchestration workflows. They will also mentor engineering teams and drive the adoption of AI-driven practices across the software development lifecycle.

Requirements

Candidates must have 10+ years of experience in production software systems and 2-4 years of hands-on experience with LLMs and generative AI. Proficiency in .NET/C#, Java, Python, and cloud platform expertise is required.

Skills

AI Engineering
LLM
Generative AI
.NET
C#
Java
Python
SQL
Git
CI/CD
API Architecture
Prompt Engineering
RAG Systems
Vector Databases
Agentic AI
Cloud Platforms

Benefits

Competitive compensation
Bonuses
Flexible benefits
Commissions
Stock options
Coaching
Career opportunities

Visa sponsorship

Not detected in the job text

Keywords

AI Engineering
LLM
Generative AI
.NET
C#
Java
Python
SQL
Git
CI/CD
Azure
AWS
GCP
Docker
Kubernetes
API
Prompt Engineering
RAG
Vector Databases
Agentic AI
MCP
NLP
UiPath
SDLC
Agile
DevOps
Machine Learning
Scikit-learn
TensorFlow
PyTorch

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