We are looking for an Automation Engineer - a developer-first, agentic thinker who will build the intelligent systems that keep Sophis, 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: someone hungry to learn a complex trading system hands-on, then progressively transform how it is tested and delivered through AI-driven automation. WHAT WILL YOU DO?

- 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 containerized 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. WHAT DO YOU NEED TO SUCCEED?
- 8+ years as a software developer or automation engineer who writes production-grade code regularly.
- Must have experience working with a Banking/financial firm in a recent.
- Solid 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 Have

- 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).

Languages: Python, C++14, C#/.NET, Java, SQL, PowerShell, ksh/bash Automation: pytest, GitHub Actions, Jenkins, Artifactory, Docker, Ansible, CMake Messaging: TIBCO EMS, IBM MQ, Solace AI: GitHub Copilot, Windsurf/Cascade, LLM-based test generation Platform: Sophis/Risque, FpML Web Services, Control-M, SonarQube

📌 QA Automation Engineer (Toronto)
🏢 Compunnel
📍 Toronto