Co-create solutions with business and technical stakeholders through workshops, rapid iterations, and hands-on delivery Locate, qualify, and secure access to data required for each use case, working directly with the Data Engineer Translate use cases into production-ready GenAI and agentic AI solutions, including RAG architectures, intelligent assistants, and AI-enabled workflows Prototype, test, deploy, monitor, and improve solutions in real client environments using feedback from users and domain experts Collaborate with Data Engineers, Software Engineers, Foundations Architects, Governance experts, Business Value Advisors, and Service Delivery Managers Balance speed, quality, cost, security, and maintainability while making technical and delivery trade-offs Define success criteria including adoption, performance, reliability, risk, cost, and measurable business value Turn successful delivery into reusable patterns, accelerators, and building blocks for future engagements Typically 5-10 years of relevant experience in AI Engineering, Machine Learning, Software Engineering, Data Engineering, or technical consulting Hands-on experience delivering AI, GenAI, or software solutions into production A degree in Computer Science,



Engineering, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience Strong Python development skills API integration experience and solid software-engineering practices Hands-on experience with LLMs and GenAI, including RAG, embeddings, vector search, AI agents, and agentic workflows Familiarity with AI frameworks such as LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, or similar Experience integrating and deploying AI solutions within enterprise environments and on Azure, AWS, or GCP Working knowledge of Docker, Git, CI/CD, MLOps/LLMOps, monitoring, security, data privacy, governance, and responsible AI principles Demonstrates expertise in delivering AI and GenAI solutions, with solid capabilities in Python development, API integration, and enterprise deployment on platforms like Azure, AWS, or GCP. AI Engineering Python Development Enterprise Deployment ATS Optimization Keywords AI Engineering Machine Learning Software Engineering Data Engineering Python Development Data Privacy Responsible AI AI Frameworks AWS

📌 Remote AI Engineer (Montreal)
🏢 Jobtailor
📍 Montreal