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Toronto, Ontario, Canada
Hybrid
Element employees make a difference in the lives of others every day. We are re-defining the fleet management industry to be people first, then business – delivering on our promise of a superior client experience. This takes hard work and innovation, and we need more like-minded people on our team.
About the Role
We’re looking for a dynamic and collaborative Lead Software Engineer to join our team. In this role, you will lead end-to-end solution delivery across the Billing and Maintenance product landscape, driving modernization of maintenance operations, improving billing accuracy, and enhancing service reliability. You will serve as the overall technical and delivery lead across multiple vendor development teams, ensuring alignment between solution architecture, application development, and business objectives. This role partners closely with product, operations, vendors, and internal IT teams to deliver scalable, secure, and high-quality solutions that improve operational efficiency, revenue protection, and client experience.
Beyond traditional delivery, you will actively champion AI-assisted engineering and intelligent automation as core practices leveraging modern AI development tools and agentic capabilities to accelerate delivery, improve quality, and unlock smarter workflows across the Billing and Maintenance product landscape.
What You’ll Do
Lead end-to-end solution delivery for Billing and Maintenance applications across front end, back end, APIs/services, integrations, data layers, AI-enabled capabilities, and vendor-supported components.
Drive AI-assisted engineering as a core practice across the team — leveraging tools like GitHub Copilot, Claude, or equivalent platforms for code generation, refactoring, test authoring, debugging, documentation, and solution prototyping to meaningfully accelerate delivery.
Identify and lead practical AI, automation, and intelligent workflow opportunities across Billing and Maintenance to reduce manual effort, improve billing accuracy, detect anomalies, support decision-making, and enhance client experience.
Serve as the overall application lead, solution architecture lead, and functional SME across Billing and Maintenance initiatives from intake, design, development, testing, release, and production support.
Provide technical, functional, and delivery direction to vendor development teams, ensuring architecture, application development, AI opportunities, and business requirements are aligned to enterprise standards and product outcomes.
Translate business needs into scalable functional and technical specifications, including impact analysis, solution options, design decisions, dependencies, risks, security considerations, and effort estimates.
Lead architecture and solution design discussions, ensuring implementations meet security, performance, availability, scalability, compliance, resiliency, maintainability, data governance, and AI risk standards.
Partner with product, operations, QA, design, business stakeholders, IT, security, data, and vendor teams to refine requirements, prioritize work, manage dependencies, track deliverables, and drive Agile execution.
Establish and enforce engineering standards for clean, secure, maintainable code through design reviews, code reviews, refactoring, automated testing, CI/CD improvements, and release governance.
Act as the primary escalation and decision-making point for complex system issues during project delivery, enhancements, testing, release, production support, and incident response.
Facilitate knowledge transfer between Element IT, vendor partners, and business stakeholders while mentoring team members, promoting best practices, and maintaining API specifications, architecture notes, runbooks, support guides, and operational readiness documentation.
Basic Qualifications
8+ years of hands-on experience delivering production-grade software solutions, with strong depth in backend engineering, APIs/services, integrations, data layers, and cloud-native application delivery.
3+ years of technical leadership experience, including leading solution design, breaking down work, mentoring engineers, guiding vendor development teams, and driving code quality through reviews and engineering standards.
Strong proficiency in at least one modern backend language/framework (e.g., Java/Spring Boot, Node.js, or Python), with 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 AWS, including containerized workloads (Kubernetes/EKS, ECS), serverless services such as AWS Lambda, managed databases, and cloud security practices.
Demonstrated, hands-on use of AI-assisted development tools (e.g. GitHub Copilot, Cursor, or Claude/ChatGPT for dev workflows) to improve engineering productivity across the SDLC.
Bachelor’s degree in computer science, Software Engineering, or a related discipline, or equivalent practical experience.
Strong hands-on understanding of DevOps and cloud-native delivery practices, including CI/CD pipelines, infrastructure as code, automated deployments, observability, release management, and production reliability.
Preferred Qualifications
Frontend development experience using modern frameworks such as React, Angular is an added advantage.
Hands-on experience or strong working knowledge of Agentic AI solutions, including AI agents, workflow automation, LLM integration, prompt orchestration, tool/function calling, human-in-the-loop controls, and responsible AI practices.
Ability to effectively use AI-assisted development tools to improve engineering productivity, including code generation, debugging, refactoring, test creation, documentation, and solution prototyping while maintaining code quality, security, and compliance standards.
Experience with observability practices including logging, metrics, tracing, alerting, dashboards, and production health monitoring.
Strong understanding of secure-by-design practices, including authentication, authorization, secrets management, vulnerability remediation, OWASP fundamentals, and data protection.
Experience evaluating or integrating AI/ML platforms, copilots, third-party AI services, or intelligent automation solutions into enterprise applications.
Location
Toronto. Our Mississauga office will move to 1 Adelaide in Toronto in September 2026.
The hiring base salary range for this position is $111,100 - $152,800 annually. Actual compensation within this range will be dependent upon the individual’s knowledge, skills, experience, equity with other team members, and alignment with market data. Please note that the disclosed salary range is solely for candidates hired to perform work within this
What’s in it for You
• A culture of innovation, empowerment, decision-making, and accountability
• Comprehensive health and welfare benefits that serve the needs of you and your family and foster a culture of wellness (for qualified roles)
• Additional benefits and amenities, including paid time-off programs (vacation, sick leave, and holidays) (for qualified roles)
Applicants will be required to undergo a background check only if and after a conditional offer of employment has been extended.
Element Fleet Management and its wholly owned subsidiaries are an equal opportunity employer committed to diversity, equity, inclusion, and belonging. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, genetic information, sex, gender identity, sexual orientation, age, marital status, family status, ancestry, national origin, citizenship, physical or mental disability, veteran status, military obligations or any other characteristic protected by federal, state and local laws. Disability-related accommodations during the application and interview process are available upon request. Should you require an accommodation with our hiring process please send an email to talentacquisition@elementcorp.com or call (800) 665-9744. Element Fleet Management also uses AI-assisted tools to help screen and assess applications. These tools analyze information you provide (for example, your rēsumē and screening responses) to identify job-related skills, qualifications, and experience. AI outputs do not by themselves determine whether you advance or receive an offer – they assist recruiters and hiring managers. Final hiring decisions are made by people.