Job Description

WHAT IS THE PROSPECT? RBC Capital Markets is a leading global investment banking company dedicated to providing services in banking, finance, and capital markets to corporations, institutional investors, asset managers, and governments globally. The Funding and Liquidity Technology group within RBC Capital Markets' Quantitative and Technology Services (QTS) organization is responsible for supporting the business units that manage both secured and unsecured funding within Capital Markets.

We’re building an internal analytics platform for institutional equities — serving Sales Traders, Portfolio Managers, and Analysts. The platform delivers real-time desk flow monitoring, research & sentiment analysis, AI-powered insights, and market intelligence within a modern, high-performance web application built on a Turborepo monorepo.

We are looking for a Senior Fullstack Engineer to design, build, and scale core features across the entire stack — from interactive frontend dashboards to backend data services and AI integration layers. You'll work closely with traders and portfolio managers to ship tools that directly impact trading decisions.

WHAT WILL YOU DO?

Build & own features end-to-end across a Next.js 16 frontend, Node.js/Express backend services, and Python/FastAPI AI service layer

Design and implement real-time data flows using WebSockets (Socket.IO), Kafka consumers, and streaming AI responses (SSE)

Develop rich, data-dense UIs — interactive charts (Highcharts), grids, dashboards with drag-and-drop widget layouts, and a conversational AI assistant panel

Architect and maintain shared packages (store, UI components, charts, types, grid, utils) within the Turborepo monorepo





Integrate with capital markets data infrastructure — KDB+/Q real-time and historical databases, time-series data pipelines, and enterprise messaging

Build and optimize the BFF proxy layer — auth-validated API proxying, token injection, and request routing to Node.js and Python services

Implement caching strategies with Redis (session store, API response cache, rate limiting) and RTK Query (tag invalidation, optimistic updates)

Work with AI/LLM integration — orchestrate context for RAG pipelines, handle streamed AI responses, and build prompt-driven features

Ensure production reliability — Kubernetes deployments via Helm, reverse proxy routing, horizontal pod autoscaling, and observability with Kibana/Grafana

Collaborate with quants, traders, and product to translate desk workflows into high-impact platform features

WHAT DO YOU NEED TO SUCCEED? Must have

5+ years of professional software engineering experience with significant full-stack development background.

Expert-level TypeScript proficiency and experience working in large, strictly-typed codebases.

Deep experience with React and Next.js, including App Router, Server Components, middleware, API routes, and SSR/ISR patterns.

Strong backend skills in Node.js, with proven expertise in Express, REST API design, middleware patterns, and async data pipelines.





Experience managing state at scale using Redux Toolkit and RTK Query, including cache tags, optimistic updates, and code-splitting slices.

Proven ability to design and implement real-time systems using WebSockets, Socket.IO, Server-Sent Events, or similar push-based architectures.

Demonstrated proficiency with MongoDB (Mongoose ODM) and Redis, including caching patterns and pub/sub implementations.

Hands-on experience with monorepo tools such as Turborepo, Nx, or Lerna for managing shared packages and build pipelines.

Experience implementing secure authentication and authorization systems, including OAuth2/OIDC, JWT, LDAP/AD integration, and session management with NextAuth.js.

Proficiency containerizing applications using Docker and deploying to Kubernetes with Helm charts, managing pod scaling, health checks, and deployment strategies.

Strong communication skills for explaining technical trade-offs to non-technical stakeholders, including trading desk teams.

Nice-to-have

Capital markets or financial services background with understanding of equities trading workflows, order flow, and desk structures.

Python/FastAPI experience for building or integrating AI/ML service layers.

Proficiency with KDB+/Q or time-series databases for querying tick data and managing real-time and historical market data.

Experience with AI/LLM integration, including RAG pipelines, prompt engineering, streaming inference, and work with frontier models such as Claude and GPT.

Expertise in charting and data visualization using libraries such as Highcharts, D3, or similar tools for financial data.

Experience with observability tooling including ELK stack,

📌 Senior Software Engineer (Toronto)
🏢 Royal Bank of Canada
📍 Toronto