Automation Engineer (Python/SQL)

Royal Bank of Canada•Toronto, ON

10h•Onsite

About The Position

We are looking for an Automation Engineer who will build the intelligent systems that keep Sophis, RBC Capital Markets’ strategic front-to-back trading platform, running at the highest quality bar. You will operate as an AI agent coordinator, software developer, and DevOps engineer in one. The platform spans pricing, transactions, cash flows, position management, risk, accounting, operations, and regulatory reporting. Your first major initiative will be leading the testing effort for the Sophis v25 platform migration: methodically comparing production benchmark outputs against the upgraded release candidate across all critical workflows.

Requirements

2–4 years as a software developer or automation engineer who writes production-grade code regularly
Strong Python skills (pytest, pandas, numpy, cx_Oracle) and comfort with SQL (Oracle and/or Sybase/SQL Server).
Hands-on experience contributing to or building CI/CD pipelines (GitHub Actions, Jenkins).
Working experience with AI-assisted development tools (Copilot, Windsurf, Cursor) and curiosity to go deeper into LLM-based automation.
Some exposure to capital markets, trading systems, or financial services — deep expertise can be built on the job.
Git proficiency: branching strategies, PR workflows, pre-commit hooks; willingness to do hands-on testing and detailed output analysis — you learn the system by testing it, not just reading about it.

Nice To Haves

Experience with agentic AI frameworks (LangChain, AutoGen, CrewAI) or custom LLM orchestration.
Exposure to Sophis/Risque or comparable front-to-back platforms (Murex, Calypso, Summit).
C++ or C# development experience; comfort with multi-language codebases.
Knowledge of messaging middleware (TIBCO EMS, IBM MQ, Solace) or enterprise scheduling (Control-M).
Unix/Linux scripting (ksh, bash, Ansible) and performance testing tools (Locust, k6, JMeter).

Responsibilities

Work alongside the team to learn Sophis end-to-end — from trade booking and pricing through EOD batch, P&L, risk, and regulatory outputs — through hands-on testing and analysis.
Analyse and compare benchmark production outputs against release candidate outputs to identify regressions, discrepancies, and behavioural changes at the data and workflow level.
Develop domain expertise in the platform’s business logic, data flows, and configuration — the foundation for every automation decision you will make; progressively transform testing from manual to automated: identify the highest-value manual tests, build repeatable automation, and retire manual steps as coverage proves reliable.
Build AI-powered test generation and regression triage using LLMs, AI coding assistants (Copilot, Windsurf/Cascade), and agentic frameworks — shipping automation at developer velocity; develop and own GitHub Actions CI/CD workflows: automation stages, quality gates, and deployment pipelines from DEV → QAT → UAT → PROD.
Engineer containerised test environments, artifact promotion via Artifactory, and IaC provisioning across Unix and Windows.
Instrument pipelines with coverage, SonarQube, and metrics dashboards; own the 80%+ coverage target as a deliverable; build internal quality tooling — libraries, CLI tools, automation frameworks — that the broader engineering team uses to test and ship faster.
Coordinate multi-team automation workflows spanning development, testing, and operations; act as the glue between code quality and operational reliability; partner with developers, platform engineers, and business analysts; grow alongside experienced capital markets technologists while contributing your AI-first perspective.
Evaluate and adopt emerging AI tooling, agent frameworks, and FinTech automation patterns to keep the team at the leading edge.