Full Stack Engineer

• Work Mode: Onsite (Day 1 onboarding onsite/in office presence 3x/week)

Summary

• Duration: 12 months
• Location: Montreal
• Work Mode: Onsite (Day 1 onboarding onsite/in office presence 3x/week)

Responsibilities

• Design, build, and operate AI-driven applications using LLMs for natural-language interaction, intelligent search, summarization, content generation, and workflow automation.
• Develop retrieval-augmented generation (RAG) solutions connecting models to enterprise data securely.
• Integrate commercial or internally hosted models through secure APIs and implement prompt management, structured outputs, and context management.
• Create evaluation datasets and automated tests for answer quality, groundedness, safety, latency, reliability, and cost.
• Build intuitive Angular interfaces and data visualizations for user interaction 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 security measures.
• Apply software engineering best practices, including code review, automated testing, CI/CD, observability, secure development, and performance tuning.
• Partner with product managers, UX/UI teams, architects, data specialists, and business stakeholders to translate requirements into technical outcomes.
• For senior candidates, lead solution design, mentor engineers, and influence standards.

Requirements

• Minimum 5 years of software engineering experience, including hands-on delivery of AI-enabled applications.
• 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, and AI security.
• Hands-on use of AI coding assistants like Claude, GitHub Copilot, with disciplined review and testing practices.
• Strong CI/CD and DevOps experience with automated builds, testing, deployment, 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.

This role is for an existing vacancy.