Associate Director – AI Engineer, QTS Architecture

What is the opportunity? We're building the agentic platform that will let every development team at RBC execute AI driven SDLC — our spec-driven, agent-assisted software delivery methodology — at scale. This is a hands‑on platform engineering role inside the Capital Market’s Architecture Team: building out our architecture-as-code system to embed in the development process for AI agents to leverage.

Job Description What is the opportunity? We're building the agentic platform that will let every development team at RBC execute AI driven SDLC — our spec-driven, agent-assisted software delivery methodology — at scale. This is a hands‑on platform engineering role inside the Capital Market’s Architecture Team: building out our architecture-as-code system to embed in the development process for AI agents to leverage.

If you're the kind of engineer who has already wired tools like Claude Code into your own workflow with custom skills and MCP servers to make yourself dramatically more productive, and you want to turn that instinct into a platform used across an entire bank, this is that role.

What will you do?

Design and build agents across focusing on the design & architecture phase: architecture as code, codified tech standards, AI context systems, and technology toil reduction from traditional CICD processes (Access, Onboarding, etc)

Integrate CALM architecture standards into the development process for building and maintaining architecture artifacts

Build these agents on coding harnesses via custom skills and tools (including MCP servers), on managed agent platforms such as Claude/Devin, and as native agents using frameworks like LangChain and LangGraph — choosing the right substrate for each use case

Implement and extend spec-driven development workflows (e.g., specify > clarify > plan > tasks > analyze > implement, in the style of GitHub spec-kit / SpecKit) as the backbone of the platform's golden path

Build the technical plumbing that enforces AI-DLC's gates (e.g. architecture drift detection, adherence to tech standards) as machine-checked controls rather than advisory guidance

Continuously push what frontier models and coding harnesses like Claude Code can automate — both at a personal productivity level and as reusable capability that scales across other development teams

Partner with DevOps, Security, and platform teams to get new agents and skills safely into production and into the shared skill/tool catalog

Evaluate emerging agentic AI platforms, frameworks, and design patterns, and make build-vs-adopt recommendations for the platform roadmap

Regularly demonstrate what you've built to other development teams — explaining not just what an agent does, but how it works — to build trust and drive adoption of the platform

Act as a hands‑on technical resource and champion for teams adopting AI-DLC, helping them get unblocked on the platform

What do you need to succeed? Must‑have:

3+ years of experience with a software development background (Python and/or TypeScript/JavaScript) with the ability to build and operate production‑grade services, not just prototypes

Hands‑on experience building agent‑based solutions — e.g., with LangChain, LangGraph, or comparable agent frameworks – even within coding harnesses like Claude Code.

Practical experience with MCP (Model Context Protocol) servers and building custom skills/tools for coding harnesses such as Claude Code

Demonstrated personal fluency with frontier coding assistants (e.g., Claude Code) for real engineering work, including multi‑agent workflows

Experience with CI/CD pipelines and DevOps tooling (e.g., GitHub Actions, Jenkins, Docker/Kubernetes) — you understand what CICD automation actually does, and how architecture can be integrated by default

Strong understanding of software development lifecycle, including product discovery, stakeholder requirements gathering, design, architecture, development, and release

Strong communicator, comfortable presenting and demoing technical work to other development teams and translating platform capabilities into terms application teams can act on

Strong software architecture and system design skills; comfortable making platform‑level tradeoffs that will be consumed by many other teams

Nice‑to‑have:

Experience with spec‑driven development paradigms, particularly GitHub spec-kit / SpecKit — a significant advantage for this role

Experience in architecture‑as‑code frameworks, particularly CALM finos

Application Architecture experience, particularly system design, data access/layer, data ontology, etc

Experience with autonomous coding agent platforms such as Devin, Claude Code, Copilot or similar products

Familiarity with AI‑DLC or comparable structured, gate‑based AI‑assisted