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We are seeking a highly experienced and technically proficient AI-First Full Stack Engineer to join our team in Mississauga. This is a critical, senior-level individual contributor role for a deep technical expert who will pioneer the integration of Artificial Intelligence into our software development lifecycle. The ideal candidate is a passionate, hands-on engineer who operates with a high degree of autonomy to solve complex problems, set technical direction, and mentor other engineers through influence and example, without direct managerial responsibilities. You will be instrumental in translating complex business challenges in the financial domain into robust, scalable, and high-performance applications, built using an AI-augmented approach.
Job Responsibility
AI-Augmented Solution Design & Implementation: Lead the end-to-end design, architecture, and hands-on implementation of complex, full-stack applications. Strategically embed AI-powered tools (e.g., Devin, GitHub Copilot, Codex) to accelerate development, automate complex tasks, and validate architectural patterns
Champion Elite Engineering Craftsmanship: Drive a culture of quality through the disciplined application of Spec-Driven Development (SDD) for clear planning, and Test-Driven (TDD) / Behavior-Driven Development (BDD) for flawless execution. Use AI to generate intelligent test cases and automate quality gates
Architect for Scale and Resilience: Provide deep expertise in modern application architecture, designing for cloud readiness by applying 12-Factor App principles and microservice patterns to build scalable and resilient systems
Technical Leadership & Mentorship: Act as a primary subject matter expert in modern software engineering. Provide technical leadership and guidance to the team, fostering best practices in AI-augmented development and scalable system design through code reviews, technical discussions, and collaborative problem-solving
Strategic Vision & Innovation: Embrace an agile, iterative mindset that avoids 'Big Up-Front Design' (BUFD). Contribute to the strategic vision for AI in engineering by researching and evaluating new AI technologies, methodologies, and tools to maintain a competitive edge
Full-Stack Problem Solving: Mastermind database interactions across Oracle and MongoDB, employing AI to analyze query performance and recommend optimizations. Work across the entire stack to resolve high-impact problems through in-depth evaluation of business and system processes
Requirements
6+ years of experience in software engineering, with at least 6 years in a senior or lead role delivering complex, enterprise-grade applications
Demonstrated success building and deploying applications in financial services, banking, or capital markets domains
Proven experience leading technical implementations and mentoring other engineers in a senior individual contributor capacity
Strong communication and stakeholder management skills
Advanced degree (or equivalent experience) in Computer Science, Engineering, or a related quantitative field is preferred
Deep, practical knowledge of designing for cloud readiness, including microservice architecture, 12-Factor App principles, and modern design patterns
Proven experience championing SDD (Spec Driven Development), TDD (Test Driven Development), and DDD (Domain Driven Design) within an agile environment
Mastery of modern Java (JDK 17/21) and the core Spring Framework (Spring Boot, Spring MVC, Spring Data JPA, Spring Cloud)
Hands-on experience with modern UI frameworks like Angular, using TypeScript/JavaScript to build intuitive user interfaces
Strong, hands-on experience with both relational (Oracle, SQL) and NoSQL (MongoDB) databases
Proficiency with modern CI/CD pipelines (e.g., Harness, Jenkins), containerization with Docker, and container orchestration platforms, specifically OpenShift and Kubernetes
Demonstrable, hands-on experience using and integrating AI development tools (e.g., Devin, GitHub Copilot, Claude, Codex) into the software development lifecycle for tasks like code generation, debugging, and documentation
Strong understanding of the concepts underpinning modern AI tools (LLMs, prompt engineering, Retrieval-Augmented Generation – RAG, MCP, A2A) and a clear vision for how to leverage them to transform engineering productivity and quality