cloud developer

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//