About this role
Job Title: Full Stack Java Developer (with DB & Cloud) Location: Montreal (day 1 onboarding onsite / in-office presence required 3x/week) Years of experience: 5-7
Core Development	 • Java: Strong hands-on experience with Java	 • Web Services: Spring Web Services and understanding of Apache CXF framework	 • Spring / Spring Boot: Strong knowledge of Spring Framework and Spring Boot for enterprise application development	 • JUnit & TDD: Strong unit testing and Test-Driven Development (TDD) experience	 • Database:	 • RDBMS (PostgreSQL): Good understanding of relational database concepts, SQL optimization, and data modeling	 • NoSQL (MongoDB): Good knowledge of NoSQL concepts and CRUD operations	 • AI & Intelligent Development: understanding of Generative AI concepts, Large Language Models (LLMs), and AI-assisted software development.	 • Experience using AI coding assistants such as GitHub Copilot, Microsoft Copilot, Cursor, or similar tools to improve developer productivity.	 • Familiarity with Prompt Engineering and effective AI interaction techniques.	 • Basic understanding of AI application patterns, including Retrieval-Augmented Generation (RAG), vector databases, and AI agent workflows.	 • Experience integrating applications with AI services and APIs (e.G., Azure OpenAI, OpenAI, Anthropic, or similar platforms).	 • Knowledge of AI governance, responsible AI principles, and secure handling of enterprise data.	 • Knowledge of the Following Will Help: Docker Kubernetes	 • Cloud Technologies (Azure preferred): Git, Angular, Ext JS, CI/CD Pipelines (Jenkins, GitHub Actions, Azure DevOps)	 • AI/ML Platforms and Services	 • Design SOLID Principles	 • Strong understanding and practical application of SOLID principles in software design.	 • Design Patterns: Familiarity with key Java design patterns and the ability to apply them effectively during software development.	 • Essential: Singleton, Factory, Template, Strategy.	 • Preferred: Observer, Builder, Adapter, Facade, Dependency Injection patterns.	 • System Design: Understanding of microservices architecture, event-driven systems, API-first design, and scalable cloud-native applications.	 • Ability to evaluate where AI capabilities can be incorporated into business workflows and applications.	 • Ability to leverage AI tools responsibly to improve development efficiency, code quality, and innovation. Nice-to-Have: Experience with LangChain, Semantic Kernel, AutoGen, MCP (Model Context Protocol), or similar AI frameworks. Exposure to vector databases, embeddings, and semantic search technologies. Experience implementing AI-powered automation, observability, or operational intelligence solutions.
*//EEO Employer: Minorities/ Females/ Disabled/ Veterans/ Gender Identity/ Sexual Orientation//*