Agentic AI Lead

AI in this role

Lead R&D and architecture for agentic AI solutions, multi-agent systems, and production machine learning pipelines.

langchainhugging-facepytorchtensorflowkeraspythonhuggingfacefastapidjangoflaskpostgresql

prompt-engineeringragai-evaluationcomputer-visionnlpagentic-aimulti-agent-systemssystem-architecturemachine-learning

Job Description

We are seeking an experienced Agentic AI Lead/Solutions Architect to drive artificial intelligence and machine learning initiatives across RBC GAM. This role requires a strategic leader who can architect Agentic AI solutions, mentor teams, and translate complex technical concepts into business value. The ideal candidate will have proven experience in Agentic AI engineering, full-stack development, and cross-functional project leadership.

What is the opportunity?

Lead R&D efforts in AI/ML applications for financial services, including document intelligence and automated decisioning systems
Architect end-to-end AI solutions from model design to scalable deployment using modern frameworks
Drive technical innovation through experimentation with cutting-edge methods including RAG, multi-agent systems, and transformer architectures
Establish and maintain deployment pipelines for AI model implementation and monitoring
Lead complex AI projects from conception to production, including solution architecture and system design
Coordinate cross-functional teams including ML engineers, backend developers, data scientists, and business stakeholders
Develop project roadmaps, load planning, and optimization strategies for AI implementations
Ensure smooth integration from prototyping to production environments
Mentor junior engineers and foster a culture of applied innovation and technical excellence
Guide team members in understanding AI/ML concepts and their business applications
Provide technical leadership in algorithm selection, model evaluation, and best practices
Support professional development through code reviews, technical writing, and knowledge sharing

What you need to succeed – Must have’s :

Programming: Expert-level Python proficiency; experience with JavaScript, SQL, and web technologies
AI/ML Frameworks: PyTorch, TensorFlow, Keras, HuggingFace Transformers, LangChain
Development: FastAPI, Django, Flask, RESTful API design and development
Data Technologies: PostgreSQL, data processing pipelines, ETL processes
Specialized AI: NLP, computer vision, retrieval-augmented generation (RAG), multi-agent systems
10+ years of professional software development or relevant research experience with strong Python background
3+ years of hands-on AI/ML engineering experience in production environments
Proven track record of leading technical teams and complex AI projects
Experience with full-stack development and system integration
Background in mentoring and developing technical talent

Nice to Have’s

Publications or research contributions in AI/ML conferences or journals
Experience in financial services or regulated industries
Experience with document processing, PDF parsing, and text extraction
Familiarity with prompt engineering and large language model optimization

What’s in it for you?

Competitive total rewards package including performance bonuses, flexible benefits, and stock where applicable
Leadership opportunity to shape modern delivery practices and influence product strategy across the organization
Supportive leaders invested in your development and career advancement
Collaborative, high-performing team environment with a focus on innovation and continuous learning
Opportunity to do challenging work and make a tangible impact on products that serve millions of customers and strengthen communities

#LI-POST

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:

RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

WEALTH MANAGEMENT

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-09-28

Application Deadline:

2026-10-23

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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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.

How we rate this

Agentic AI Lead at RBC rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRAGAI EvaluationComputer VisionNLPAgentic AIMulti Agent SystemsSystem Architecture

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide that one model's output is better than another's for a given task?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?

Adapt your resume

List these exact terms on your resume: Prompt Engineering, RAG, AI Evaluation, Computer Vision, and NLP. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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