Top Tech Jobs & Startup Jobs in Toronto

Conduct manual penetration tests and secure code reviews across web applications, APIs, AWS infrastructure, and AI systems. Develop AI-assisted security tooling, test LLM applications and agentic systems, triage SAST findings, tune security rules, support test-to-production reviews, and communicate risks to engineering teams. The role also helps establish penetration-testing standards for AI-generated software and agent workflows.

Supports and optimizes the Genesys contact center platform, including routing, IVR, omnichannel workflows, integrations, and flow logic. Troubleshoots platform incidents, monitors system performance, implements simple features, and supports voice, SMS, and email channels. Collaborates with Salesforce teams, technical support, telecom carriers, and business stakeholders to translate requirements into technical solutions and maintain reliable customer and agent experiences.

Principal Software Engineer responsible for architecting and leading development of scalable, reliable backend systems and the core fintech platform. The role sets technical direction, leads complex cross-team initiatives, promotes architectural and engineering best practices, addresses technical debt and incidents, and mentors engineers. Candidates need 10+ years of technical leadership experience, deep distributed-systems expertise, Ruby on Rails experience, strong communication and influence skills, agile development experience, and familiarity with frontend architecture or full-stack systems.

Sets the technical vision for data science, leads complex credit risk, pricing, and loss forecasting models from conception through production, and architects scalable machine learning pipelines. Partners with senior stakeholders to shape strategy, establishes modeling and validation standards, mentors technical staff, and communicates recommendations to executives. The role requires deep fintech lending experience, advanced statistical and machine learning expertise, and hands-on production model deployment.

Architects and develops AI-powered systems, backend services, APIs, experimentation frameworks, and automation using foundational models. Integrates AI capabilities with microservices, AWS, Snowflake, and diverse technology stacks while ensuring scalability, reliability, and maintainability. Collaborates with product, data science, and engineering teams to translate business needs into technical solutions, evaluate emerging AI tools, and rapidly prototype proof-of-concept applications.

Conduct manual penetration testing, secure code reviews, and SAST triage across web applications, APIs, and AWS infrastructure. Develop AI-assisted security tooling, define testing approaches for LLM applications and agentic systems, and review AI-generated software before production. Communicate vulnerabilities, risks, and remediation priorities to engineering teams while improving secure SDLC practices.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.