Lead Full Stack Software Engineer – AWS / SaaS / Applied AI

About the Role

What You’ll Do

• Build full-stack SaaS and web applications across the complete technology stack.
• Develop front-end applications with React, Next.js, Angular, TypeScript, JavaScript, HTML, CSS/SASS, and related technologies.
• Develop backend services and APIs with Java, Spring Boot, Node.js, Express.js, REST, and GraphQL.
• Design architectures, integrations, data flows, APIs, authentication, and reusable components.
• Translate stakeholder needs into technical requirements, workflows, wireframes, data models, and implementation plans.
• Build and operate cloud-native solutions using AWS.
• Deploy applications with Docker and Kubernetes and automate delivery with Terraform, GitHub Actions, Jenkins, and CI/CD.
• Work with relational and NoSQL databases, including PostgreSQL, MySQL, SQL Server, and MongoDB.
• Implement secure architectures using OAuth2, OIDC, JWT, RBAC, encryption, access controls, and OWASP practices.
• Develop automated tests and participate in reviews, troubleshooting, and continuous improvement.
• Collaborate with product, UX, QA, architecture, engineering, business, and customer-facing stakeholders.
• Mentor developers and evaluate practical applications of AI, machine learning, NLP, computer vision, and LLMs.

Required Qualifications

• At least 5 years of professional experience in software engineering, full-stack development, technical consulting, or a related role.
• Master’s degree in Computer Science, Software Engineering, or an equivalent technical discipline.
• Strong front-end development experience with modern JavaScript and TypeScript technologies.
• Strong backend development experience with Java, Spring Boot, Node.js, Express.js, REST APIs, and API integrations.
• Experience delivering production-grade full-stack applications and AWS cloud-native solutions.
• Working knowledge of Docker, Kubernetes, Linux, Git, CI/CD, and modern DevOps practices.
• Experience with relational databases and SQL, including PostgreSQL, MySQL, or SQL Server.
• Understanding of scalable architecture, microservices, design patterns, maintainability, and system integration.
• Experience with automated testing, regression testing, code reviews, and quality practices.
• Understanding of secure application development and API security practices.
• Experience working in Agile/Scrum environments.
• Ability to own technical work, communicate effectively, mentor developers, and support engineering decisions.

Applied AI and Data Experience

• Practical exposure to Python, scikit-learn, TensorFlow, Keras, deep learning, NLP, computer vision, LLM fundamentals, or data integration and modeling is valuable.
• The role does not require a dedicated Machine Learning Engineer but requires comfort evaluating and implementing suitable AI-enabled capabilities.

Preferred Background

• Experience in SaaS, financial services, insurance, technology consulting, enterprise software, cloud modernization, digital transformation, or data-intensive applications is valuable.
• Experience with regulated or security-conscious organizations is considered an asset.

Work Location

• The position is based in Toronto, Ontario, with a hybrid work arrangement in Toronto District.

Compensation

• Pay is listed as $61,197.71 to $142,098.92 per year.