TMC Canada
Full-Stack Java Developer (with DB & Cloud)
Full-stack Java developer building cloud-native, microservices-based applications for a research technology department using Java/Spring Boot, PostgreSQL/MongoDB, and Angular/React frontends. Heavy emphasis on AI-assisted development: integrating LLM services (RAG, vector databases) and using AI coding tools responsibly.
- Compensation
- Not disclosed
- Location
- Montréal, Canada
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Contract
- Experience
- Not specified
- Category
- Fullstack
- Posted
Skills
Must have
- Strong hands-on experience with Java
- Spring Web Services and understanding of Apache CXF framework
- Strong knowledge of Spring Framework and Spring Boot for enterprise application development
- Strong unit testing and Test-Driven Development experience (JUnit & TDD)
- Good understanding of relational database concepts, SQL optimization, and data modelling (PostgreSQL)
- Good knowledge of NoSQL concepts and CRUD operations (MongoDB)
- Understanding of Generative AI concepts, Large Language Models, and AI-assisted software development
- Experience using AI coding assistants such as GitHub Copilot, Microsoft Copilot, Cursor, or similar tools
- Familiarity with prompt engineering and effective AI interaction techniques
- Basic understanding of AI application patterns including RAG, vector databases, and AI agent workflows
- Experience integrating applications with AI services and APIs such as Azure OpenAI, OpenAI, Anthropic, or similar platforms
- Knowledge of AI governance, responsible AI principles, and secure handling of enterprise data
- Strong understanding of and practical application of SOLID principles in software design
- Familiarity with key Java design patterns (Singleton, Factory, Template, Strategy, Observer, Builder, Adapter, Facade, Dependency Injection)
- 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
Nice to have
- Knowledge of Docker, Kubernetes, Azure cloud technologies, Git, Angular, Ext JS, CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps), and AI/ML platforms
- Experience with LangChain, Semantic Kernel, AutoGen, MCP, vector databases, embeddings, semantic search, AI-powered automation, or observability solutions (nice-to-have)
Full description
Research Technology, part of IST, follows an agile delivery model. New application development is typically based on a microservices architecture and designed for cloud-native deployments. The standard technology stack includes PostgreSQL or MongoDB for data storage, Java (Spring Boot) for the middle tier, and Angular, React, or Ext JS for frontend development.
- Work on multiple initiatives within the Research Technology department;
- Core Development: Java, Spring Web Services, Apache CXF, Spring Framework, Spring Boot, JUnit, and Test-Driven Development;
- Database: PostgreSQL, relational database concepts, SQL optimization, data modeling, MongoDB, NoSQL concepts, and CRUD operations;
- AI & Intelligent Development: Generative AI concepts, Large Language Models, AI-assisted software development, prompt engineering, RAG, vector databases, AI agent workflows, and AI service integrations;
- Apply responsible AI practices, AI governance principles, and secure handling of enterprise data.
What do we expect from you ?
The minimum required skills necessary for this role :
- 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 experience ;
- RDBMS (PostgreSQL) : Good understanding of relational database concepts, SQL optimization, and data modelling;
- NoSQL (MongoDB) : Good knowledge of NoSQL concepts and CRUD operations ;
- AI & Intelligent Development : Understanding of Generative AI concepts, Large Language Models, 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, vector databases, and AI agent workflows ;
- Experience integrating applications with AI services and APIs such as 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, Azure cloud technologies, Git, Angular, Ext JS, CI/CD pipelines including Jenkins, GitHub Actions, and Azure DevOps, and AI/ML platforms and services ;