Summary
✨ AI‑Generated
A Montreal-based technology team is hiring a mid-level or senior Full Stack Engineer with AI engineering experience. Angular and Java are the primary technical skills, supported by strong CI/CD and modern software delivery experience. You will design, build, test, deploy, and operate secure, high-quality applications across the full technology stack, with emphasis on Angular front-end, Java and Spring Boot back-end, RESTful APIs, and CI/CD automation, while applying LLM capabilities to deliver AI-driven user experiences such as natural-language interaction, intelligent search, summarization, and content generation. The position is hybrid with 3 days per week onsite in Montreal.
Highlights
Mid to senior full-stack role focused on Angular and Java with AI engineering exposure; Montreal-based hybrid schedule (3 days onsite); modern software delivery with strong CI/CD; opportunity to deliver LLM-powered user experiences.
Description
We are looking for a mid-level or senior Full Stack Engineer with AI engineering experience to join our team .
Angular and Java are the primary technical skills for this role, supported by strong CI/CD and modern software delivery experience.You will design, build, test, deploy, and operate secure, high-quality applications across the full technology stack.
The role is primarily focused on Angular front-end development, Java and Spring Boot backend engineering, RESTful APIs, and CI/CD automation, while applying LLM capabilities to deliver AI-driven user experiences.
You will translate business problems into pragmatic solutions and collaborate with engineering, product, architecture, cybersecurity, and business teams to ship reliable features.
Location: Montreal (Day 1 onboarding onsite/in office presence 3x/week)
What you will do:
Design, build, and operate AI-driven applications that use LLMs for natural-language interaction, intelligent search, summarization, content generation, and workflow automation.Develop retrieval-augmented generation (RAG) solutions that securely connect models to enterprise data using embeddings, vector search, metadata filtering, citations, and access controls.Integrate commercial or internally hosted models through secure APIs and implement prompt management, structured outputs, tool or function calling, context management, and streaming responses.Create evaluation datasets and automated tests for answer quality, groundedness, safety, latency, reliability, and cost; use production telemetry and user feedback to improve the system.Build intuitive Angular interfaces and data visualizations that allow users to search, filter, review, and interact with risk, metric, policy, and control information.Design scalable Java and Spring Boot services, RESTful APIs, and event-driven or microservices-based components with appropriate authentication and authorization.Use Claude, GitHub Copilot, and similar AI engineering tools responsibly for code exploration, implementation, refactoring, test generation, debugging, review, and documentation while independently validating generated output.Apply software engineering best practices, including code review, automated testing, CI/CD, observability, secure development, performance tuning, and production support.Partner with product managers, UX/UI teams, architects, data specialists, and business stakeholders to identify high-value use cases and translate requirements into measurable technical outcomes.For senior candidates, lead solution design, mentor engineers, influence standards, assess trade-offs across model quality, latency, cost, security, and maintainability, and drive delivery across teams.Skills & Qualifications:
5+ years of software engineering experience, including hands-on delivery of production or production-like AI-enabled applications.Primary skills: Strong full-stack development experience with Angular and TypeScript, Java and Spring Boot, RESTful APIs, distributed systems, and secure application design.Practical experience with LLM application patterns, model APIs, RAG, embeddings, vector search, prompt design, structured outputs, tool calling, evaluation, observability, and AI security.Hands-on use of Claude, GitHub Copilot, or comparable AI coding assistants, with disciplined review, testing, and security practices.Strong CI/CD and DevOps experience covering automated builds, testing, code-quality and security checks, deployment, release controls, and production monitoring; familiarity with Docker, Kubernetes, and cloud-native platforms is preferred.Experience with Python, SQL or NoSQL databases, data integration, caching, and data-intensive applications.Strong problem-solving, communication, and stakeholder-management skills; senior candidates should also demonstrate architecture leadership, delivery ownership, and mentoring experience.