Top Tech Jobs & Startup Jobs in Toronto

Design, develop, modernize, and maintain enterprise applications and secure RESTful APIs using C#, .NET, ASP.NET Core, and SQL Server. Collaborate across the application stack with React, Angular, or similar frameworks; improve legacy systems, performance, reliability, and security. Participate in technical design, code reviews, automated testing, CI/CD, Docker deployments, troubleshooting, and Agile delivery. Contribute to AI-assisted engineering practices, documentation, mentoring, and continuous improvement.

Design and maintain Azure DevOps CI/CD pipelines for enterprise data and analytics platforms. Automate deployments of Microsoft Fabric, Azure Data Factory, Synapse Analytics, Databricks, and Power BI assets. Manage Azure infrastructure, security controls, identity, secrets, monitoring, logging, and infrastructure as code using Bicep or ARM Templates. Collaborate with architects, developers, and platform engineers to improve reliability, operational efficiency, and delivery automation.

Design and build AI security tools, conduct penetration testing and red teaming, assess AI applications and third-party technologies, and establish secure development standards. Integrate automated security testing into CI/CD pipelines, evaluate risks such as prompt injection and data leakage, troubleshoot production systems, and collaborate with engineering, security, customers, vendors, and business stakeholders.

Build and maintain scalable backend applications and REST APIs using Java and/or Python. Integrate AI-powered workflows, automation, and LLM capabilities into enterprise financial services applications. Develop system integrations, manage technical deliverables from design through implementation, collaborate with business and technology stakeholders, and maintain code quality while adapting to evolving technical environments.

Design, develop, test, and maintain full-stack digital platforms using Python, Django, Angular, PostgreSQL, AWS, REST APIs, and microservices. Build CMS capabilities with Wagtail, integrate databases and messaging systems, and contribute to CI/CD, automated testing, code reviews, and cloud deployment. Collaborate with product, architecture, business analysis, and engineering teams to translate evolving financial-services requirements into scalable, maintainable solutions.

Build, maintain, and execute automated functional, integration, and regression tests using SmartBear TestComplete, ReadyAPI, and Playwright. Test Java Spring applications across Linux and Windows environments, validate relational database data, investigate defects, maintain test assets, and collaborate with developers throughout the Agile lifecycle to support reliable application modernization and releases.

Modernize legacy Unix/Linux applications and scripts through refactoring, automation, containerization, and cloud migration. Develop automation with Bash, PowerShell, Python, and Groovy; deploy applications using Docker, OpenShift, Kubernetes, and AWS; and troubleshoot across Linux and Windows environments. Support application modernization involving JBoss, Tomcat, Nginx, HAProxy, and legacy Java applications while collaborating with development and technology teams on enterprise migration initiatives.

Modernize legacy Java platforms by refactoring Java 6/8, JBoss, and Struts applications toward JDK 17, Spring Boot, microservices, and cloud-native deployments. Develop backend services, TypeScript components, and integrations with enterprise authentication systems. Containerize and deploy applications using Docker, OpenShift, Kubernetes, and AWS. Contribute across the Agile lifecycle, including design, development, testing, CI/CD, deployment, and production releases while maintaining system security, stability, and continuity.

Build and deploy production-ready AI agents and agentic solutions for clients. Translate business requirements into AI applications through prototyping, testing, demonstrations, iteration, and deployment. Collaborate with stakeholders and cross-functional teams while adapting solutions to client architectures and platforms such as Snowflake and Databricks.

Coach client teams in AI product management and Product Owner practices. Identify and prioritize AI use cases, translate opportunities into measurable business outcomes, and guide products through delivery, ownership, maintenance, adoption, and continuous improvement. Build sustainable product capabilities by bridging AI and business discussions, influencing stakeholders, and enabling teams to independently manage AI-enabled applications. The role requires consulting experience, strong stakeholder communication, and a track record of delivering valuable AI products or use cases.