Design, build, and deploy end-to-end AI-powered applications and agentic systems. Integrate LLMs and RAG/vector search, develop APIs and UIs, operationalize models, and own CI/CD, containerization, monitoring, and reliability. Mentor engineers, contribute to architecture, and partner with product and security teams to ensure scalable, secure AI production systems.
Full Stack & AI Application Development •Design and build end-to-end AI-powered applications using modern frontend and backend frameworks. •Integrate LLM and agentic AI components into user-facing and system-facing workflows. •Develop APIs and services that support agent orchestration, tool calling, and workflow execution. •Build intuitive UIs for AI-assisted workflows, human-in-the-loop interactions, and monitoring. Agentic AI & Production Systems. Work with ML/Data teams to operationalize models and agentic systems into production. Implement RAG pipelines, vector search integration, and AI inference layers. Handle model lifecycle concerns: versioning, configuration, evaluation hooks, and rollout strategies. Build safeguards, validations, and fallback mechanisms for AI-driven workflows. DevOps, Reliability & Scale Own CI/CD pipelines, containerization, and deployment of AI applications. Ensure systems meet performance, scalability, security, and reliability requirements. •Implement logging, monitoring, alerting, and cost visibility for AI and application components. •Collaborate with platform and security teams to ensure compliance and operational readiness. Architecture & Collaboration. Contribute to system and application architecture decisions for AI platforms. •Write clean, maintainable, well-tested code and review contributions from peers. •Mentor engineers and raise the bar on engineering and AI delivery practices. •Partner with product and business teams to translate requirements into technical solutions. •7+ years of hands-on experience as a Full Stack Engineer or Senior Software Engineer. •Strong proficiency in backend development Python. Strong experience with modern frontend frameworks React. •Hands-on experience integrating AI/ML or LLM-based services into applications. •Solid understanding of REST APIs, microservices, and distributed systems. Design and build end-to-end AI-powered applications using modern frontend and backend frameworks.
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What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
