Lead Software Engineer
On-site · Toronto, Ontario, Canada
Job Summary
Lead end-to-end solution delivery for Billing and Maintenance applications, guiding front-end, back-end, APIs/services, integrations, and data layers across multiple vendor teams. Drive AI-assisted engineering as a core practice to accelerate delivery, improve billing accuracy, and enhance client experience. Serve as the overall application and solution-architecture lead, translating business needs into scalable specifications, enforcing engineering standards, and collaborating with product, operations, QA, design, security, data, and vendors to align with enterprise standards and product outcomes. Mentor team members, facilitate knowledge transfer, and ensure production readiness and secure-by-design practices.
Required Qualifications
- 8+ years of hands-on experience delivering production-grade software solutions with backend, APIs/services, integrations, data layers, and cloud-native delivery.
- 3+ years of technical leadership experience including leading solution design, mentoring engineers, guiding vendor teams, and driving code quality through reviews and engineering standards.
- Bachelor’s degree in computer science, Software Engineering, or related discipline, or equivalent practical experience.
- Strong proficiency in at least one modern backend language/framework (Java/Spring, Node.js, or Python) and experience designing scalable REST/GraphQL APIs, microservices, event-driven services, and integration patterns.
- Hands-on experience designing, building, deploying, and operating cloud-native applications on Azure, AWS, or GCP with containers, Kubernetes, serverless, managed databases, and cloud security practices.
- Strong understanding of DevOps and cloud-native delivery practices including CI/CD pipelines, infrastructure as code, automated deployments, observability, release management, and production reliability.
- Experience with security practices (authentication/authorization, Secrets management, vulnerability remediation, OWASP) and data protection.
- Experience evaluating or integrating AI/ML platforms, copilots, third-party AI services, or intelligent automation into enterprise applications.
- Preferred: Frontend experience with modern frameworks (React, Angular, Vue) and hands-on knowledge of AI agents, workflow automation, LLM integration, prompt orchestration, and responsible AI practices.
- Ability to leverage AI-assisted development tools to improve engineering productivity while maintaining code quality, security, and compliance.
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