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Axelon Services Corporation

Application Development

Montreal, QC, Canada

Pay: $65.52 USD / hour
Apply by: Oct 28, 2026
Experience: Minimum 5 years of hands-on experience with Java.
Posting language: English
Posted: Sep 28, 2026

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Original job description

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.

Apply About employer

More about this job

Responsibilities

Develop cloud-native applications using microservices architecture and contribute to multiple initiatives within the Research Technology department. Collaborate with Agile/Scrum teams and integrate AI capabilities into business workflows and applications.

Requirements

Requires at least five years of hands-on Java experience, strong Spring and Spring Boot skills, and experience with testing, relational and NoSQL databases, and microservices. Candidates should also understand generative AI and responsible AI practices, have experience with AI coding assistants and AI service integrations, and demonstrate strong communication, problem-solving, and ownership.

Skills

Java
Spring Framework
Spring Boot
Microservices
JUnit
Test-Driven Development
PostgreSQL
MongoDB
Generative AI
Large Language Models
Prompt Engineering
AI Service Integration
SOLID Principles
Design Patterns
Agile/Scrum
Cloud-Native Development

Visa sponsorship

Not detected in the job text

Keywords

Java
Spring Framework
Spring Boot
Spring Web Services
Apache CXF
JUnit
Test-Driven Development
PostgreSQL
SQL Optimization
MongoDB
Generative AI
Large Language Models
GitHub Copilot
Microsoft Copilot
Prompt Engineering
Azure OpenAI
OpenAI
Anthropic
AI Governance
Responsible AI
SOLID Principles
Design Patterns
Microservices
Event-Driven Systems
API-First Design
Docker
Kubernetes
Azure
CI/CD
Vector Databases

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