Senior Staff Engineer – Agentic AI
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Senior Staff Engineer – Agentic AI
Location
TORONTO, Ontario, Canada
Experience
Senior
Posted
Jul 10, 2026
Apply by
July 31, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
**Job Description**
**What's the opportunity?**
We're looking for a Senior Staff Engineer with strong hands-on engineering experience and a consulting mindset who will lead workstreams, drive stakeholder engagement, and deliver production-grade agentic AI solutions across RBC. This role bridges deep technical delivery with business advisory capability where you're as comfortable facilitating a discovery session with a business leader as you are writing production code for a multi-agent system.
At RBC Borealis, you'll be joining the Agentic AI Enablement team, a forward-deployed engineering force that embeds directly into strategic use cases across Lines of Business. You'll operate as a Tech Lead within squads, independently driving workstreams while partnering with Principal Engineers on broader engagement strategy. You'll work directly with business stakeholders, platform engineers, and LoB technical teams to deliver high-impact solutions and build organizational capability in agentic AI.
**Your responsibilities include:**
- Leading technical workstreams within engagements, including solution design, hands-on build, and delivery of production-grade agentic AI systems
- Conducting discovery sessions with LoB stakeholders to understand business challenges, identify automation opportunities, and translate requirements into agentic AI solution specifications
- Serving as Tech Lead on Light squad engagements with fractional Principal oversight, owning architecture decisions and delivery outcomes for bounded-scope solutions
- Designing and implementing end-to-end agentic solutions including MCP servers, RAG pipelines, agent orchestration, tool integrations, and security/compliance controls
- Facilitating technical workshops and presenting solution trade-offs to non-technical stakeholders with clarity and confidence
- Mentoring Staff Engineers within the pod, providing code reviews, pairing on complex problems, and supporting their professional growth
- Contributing to knowledge transfer and enablement activities, including documentation, patterns, playbooks, and hands-on training for LoB engineering teams
- Acting as a bidirectional bridge between LoB teams and Borealis platform engineering, surfacing capability gaps and informing platform roadmap priorities
- Supporting production deployments, post-deployment optimization, and contributing reusable components back to shared platforms and repositories
- Participating in community of practice activities to share learnings, identify cross-engagement synergies, and shape reference architectures
**You're our ideal candidate if you have:**
- 8-12 years of combined experience in software engineering, solutions architecture, technical consulting, or enterprise AI/ML systems
- One or both of the following:
- Consulting/advisory depth: 3+ years in technical consulting, solutions engineering, professional services, or customer-facing delivery roles where you owned the client relationship and shaped technical approaches to business problems
- Agentic AI depth: 2-4 years hands-on experience with agentic AI systems, LLMs, and modern AI/ML frameworks including architecture patterns (ReAct, Tool Use, multi-agent orchestration)
- Strong software engineering fundamentals with ability to write clean, maintainable production code (Python preferred)
- Demonstrated ability to sit across from a business stakeholder, ask the right questions, and translate ambiguous problems into structured technical approaches
- Proficiency in (or ability to rapidly acquire) LLM-based systems including prompt engineering, RAG pipelines, vector databases, and tool integration patterns
- Experience designing or implementing Model Context Protocol (MCP) servers or similar integration frameworks
- Knowledge of cloud platforms (AWS, Azure, or GCP) and modern DevOps practices including containerization (Docker, Kubernetes) and CI/CD pipelines
- Understanding of security best practices, data governance, and compliance requirements in regulated environments
- Strong facilitation, communication, and presentation skills. You can run a room, present trade-offs to executives, and write a crisp recommendation
- Proven ability to mentor junior engineers and build team capability while maintaining hands-on delivery (60-70% hands-on coding expected)
- Fast learner comfortable with ambiguity. You thrive in rapidly evolving technology landscapes and can get productive quickly in new domains
- Comfort working in Agile environments with iterative delivery approaches
**Nice to have:**
- Background in financial services, fintech, or other regulated industries
- Experience in technology consulting, solutions engineering, or customer-facing ML/AI delivery roles
- Experience leading small teams in delivery settings
- Familiarity with enterprise architecture governance processes and frameworks
- Experience with agentic AI evaluation frameworks, observability, and production monitoring
**What's in it for you?**
- Join a strategic team driving RBC’s enterprise AI transformation and competitive positioning
- Work on cutting-edge agentic AI technology with access to leading researchers, rich datasets, and significant computational resources
- Contribute to high-visibility, high-value business initiatives across the enterprise
- Leaders who support your development through mentoring and career growth opportunities
- Build deep expertise in agentic AI under guidance from experienced Principal Engineers
- Comprehensive Total Rewards Program including competitive compensation, bonuses, flexible benefits, and stock options where applicable
**About the AI Group**
RBC's AI Group is the AI accelerator for RBC, with a focus on driving the shift from early-stage AI projects to scaled, client outcomes that amplify the impact of RBC's people. In addition to helping scale the biggest AI opportunities at RBC, the AI Group is responsible for advancing research into emerging use cases across generative and agentic AI, while maintaining expertise in security, responsible AI and regulatory expectations. The Business Enablement function within the AI Group partners with LOBs and Functions to set AI ambition, originate transformation opportunities, and frame programs for delivery ensuring RBC remains at the frontier of AI-enabled value creation.
**Inclusion and Equal Opportunity Employment**
RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.
#LI-POST
#TECHPJ
**Job Skills**
Big Data Analytics, Client Counseling, Coaching Others, Critical Thinking, Decision Making, Industry Knowledge, Machine Learning (ML), Software Engineering, Software Product Design
**Additional Job Details**
**Address:**RBC WATERPARK PLACE, 88 QUEENS QUAY 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:**2026-07-09**Application Deadline:**2026-07-31
**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](https://jobs.rbc.com/ca/en).
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.
Key Responsibilities
- Lead technical workstreams including solution design, hands-on build, and delivery of production-grade agentic AI systems
- Conduct discovery sessions with business stakeholders to identify automation opportunities and translate requirements into solution specifications
- Serve as Tech Lead on Light squad engagements, owning architecture decisions and delivery outcomes
- Design and implement end-to-end agentic solutions including MCP servers, RAG pipelines, and agent orchestration
- Facilitate technical workshops and present solution trade-offs to non-technical stakeholders
- Mentor Staff Engineers through code reviews, pairing, and professional growth support
- Contribute to knowledge transfer activities including documentation, patterns, and training
- Act as a bridge between business teams and platform engineering to inform roadmap priorities
- Support production deployments, post-deployment optimization, and reusable component development
Skills Required
PythonLLMsPrompt engineeringRAG pipelinesVector databasesTool integrationModel Context Protocol (MCP)AWSAzureGCPDockerKubernetesCI/CDAgileConsulting mindsetStakeholder engagementFacilitationCommunicationPresentation skillsMentoringProblem solvingAdaptabilityFinancial services domain knowledgeFintech experienceEnterprise architecture governanceAgentic AI evaluation frameworksObservability toolsProduction monitoringLeadershipTeam building
Benefits
- Competitive compensation
- Bonuses
- Flexible benefits
- Stock options
- Mentoring and career growth opportunities
- Access to leading researchers and computational resources
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