Application Development

Summary:

• Location: Montreal
• Work Mode: Hybrid (day 1 onboarding onsite, in-office presence required 3x/week)
• This role is for an existing vacancy.

Responsibilities:

• Work on multiple initiatives within the Research Technology department.
• Develop new applications based on a microservices architecture designed for cloud-native deployments.
• Collaborate with Agile/Scrum teams to deliver solutions efficiently.
• Integrate AI capabilities into business workflows and applications.

Requirements:

• Minimum 5 years of hands-on experience with Java.
• Strong knowledge of Spring Framework and Spring Boot for enterprise application development.
• Experience with Spring Web Services and understanding of Apache CXF framework.
• Strong unit testing and Test-Driven Development (TDD) experience using JUnit.
• Good understanding of relational database concepts, SQL optimization, and data modeling with PostgreSQL.
• Good knowledge of NoSQL concepts and CRUD operations with MongoDB.
• Understanding of Generative AI concepts, Large Language Models (LLMs), and AI-assisted software development.
• Experience using AI coding assistants such as GitHub Copilot or Microsoft Copilot.
• Familiarity with Prompt Engineering and effective AI interaction techniques.
• Experience integrating applications with AI services and APIs (e.g., Azure OpenAI, OpenAI, Anthropic).
• Knowledge of AI governance, responsible AI principles, and secure handling of enterprise data.
• Strong understanding and practical application of SOLID principles in software design.
• Familiarity with key Java design patterns such as Singleton, Factory, Template, and Strategy.
• Understanding of microservices architecture, event-driven systems, API-first design, and scalable cloud-native applications.
• Excellent communication and stakeholder collaboration skills.
• Strong work ethic and ownership mindset.
• Continuous learning mindset with interest in emerging technologies, particularly AI and automation.
• Strong problem-solving and analytical skills.

Preferred Skills:

• Experience with Docker and Kubernetes.
• Familiarity with Cloud Technologies (Azure preferred), Git, Angular, Ext JS, CI/CD Pipelines (Jenkins, GitHub Actions, Azure DevOps).
• Experience with AI/ML Platforms and Services.
• Experience with design patterns such as Observer, Builder, Adapter, Facade, Dependency Injection.
• 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.