Artificial Intelligence Engineer

Title: AI/ML EngineerSalary Range: $115K–$140KLocation: Montreal, Quebec, Canada — Hybrid (3 days per week onsite)Type of Role: Full-TimeAuxo Recruitment is supporting a fast-growing startup building AI-powered products for the financial services industry. By combining financial data aggregation with advanced AI, the company is creating tools that simplify daily workflows and help advisors deliver highly personalized services to their clients.Following the recent hire of a Senior AI/ML Engineer, the team is now looking to add a Junior–Intermediate AI/ML Engineer to strengthen execution, accelerate feature delivery, and support production deployment of next-generation AI products.What You’ll Be DoingCollaborate with senior engineers to design and develop AI-driven systems, focusing on generative AI and agentic capabilities.Support the implementation of LLM-based systems to enhance financial insights and user experience.Contribute to building and improving RAG-based chatbots, financial data extraction tools, and AI-powered automation features.Maintain and evolve data pipelines for ingestion, processing, and schema evolution.Participate in benchmarking and testing LLM models (Gemini, Claude, GPT, etc.) to ensure performance and scalability.Work closely with backend and data engineers to ensure seamless microservice integration and deployment.Stay up to date with AI/ML trends — especially in generative AI, embeddings, and context engineering.Who You Are2–6 years of experience designing or deploying AI/ML systems in production.Strong foundation in Python and familiarity with FastAPI or equivalent frameworks.Experience integrating with major LLM APIs (OpenAI, Anthropic, Gemini, etc.).Basic understanding of RAG, embeddings, or context retrieval methods — or the curiosity and drive to learn them quickly.Familiar with cloud platforms (AWS, Azure, or GCP) and containerization (Docker).Good grasp of data pipelines, microservice architectures, and API-based systems.Excellent problem-solving and collaboration skills — comfortable working in a small, fast-paced team.Fintech or data-heavy application experience is an asset but not required.Nice-to-HavesHands-on experience with benchmarking or evaluation frameworks for LLMs.Experience with LangChain or agent-based systems.Exposure to multilingual NLP or structured data extraction.