Agentic AI Platform Engineer — Build Scalable SDLC Platform

RBC; Bedford; On-site; CAD 120,000 - 160,000; Full time

Benefits offered by this job

Bonuses

Stock options

Flexible benefits

Job summary

RBC is seeking a platform engineer in Bedford, Canada, to build an agentic AI-enabled SDLC harness used across the bank. You will design and deploy production-grade agents, manage skills and tooling, and integrate MCP servers for scalable automation.

You will work with DevOps, security, and platform teams, champion AI-DLC adoption, and continuously enhance the platform with frontier models and reusable capabilities for many development teams.

Qualifications

• Strong software development background with production-grade services.
• Hands-on experience building agent-based solutions and workflows.
• Practical experience with MCP servers and custom skills/tools.
• Fluency with frontier coding assistants for real engineering work.
• Experience with CI/CD pipelines and DevOps tooling.
• Understanding of the broader SDLC and architecture.

Responsibilities

• Design and build agents across the full software delivery lifecycle.
• Build agents on coding harnesses and native frameworks.
• Extend spec-driven development workflows as backbone of platform.
• Implement platform gates as machine-checked controls.
• Push frontier models and coding harness automation at scale.
• Collaborate with DevOps, security, and platform teams to ship safely.
• Evaluate AI platforms and make build-vs-adopt recommendations.
• Demonstrate platform capabilities to teams and drive adoption.
• Serve as a hands-on technical resource for teams adopting AI-DLC.

Skills

Python

TypeScript

JavaScript

Strong communication

Platform engineering

Tools

LangChain

LangGraph

Claude Code

MCP servers

DevOps tooling

GitHub Actions

Docker

Kubernetes

Job description

RBC is seeking a platform engineer in Bedford, Canada, to build an agentic AI-enabled SDLC harness used across the bank. You will design and deploy production-grade agents, manage skills and tooling, and integrate MCP servers for scalable automation.

You will work with DevOps, security, and platform teams, champion AI-DLC adoption, and continuously enhance the platform with frontier models and reusable capabilities for many development teams.