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 Git

Hub 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.

Robust 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, Git

Hub Actions, Azure Dev

Ops).

Experience with AI/ML Platforms and Services.

Experience with design patterns such as Observer, Builder, Adapter, Facade, Dependency Injection.

Experience with Lang

Chain, Semantic Kernel, Auto

Gen, 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.

📌 Application Development (Montreal)
🏢 Axelon Services
📍 Montreal