Title: Senior AI/ML Engineer

Salary Range: $120K–$175K

Location: Montreal, Quebec, Canada — Hybrid (3 days per week onsite)

Type of Role: Full-Time

Auxo Recruitment is supporting a fast-growing startup that is 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 enable advisors to deliver highly personalized service to their clients.

The team is expanding and looking to hire 2 new Sr. AI/ML Engineers, ideally one senior and one intermediate, to accelerate product development and strengthen technical leadership.

What You’ll Be Doing

• Lead the design, development, and optimization of AI-driven systems with a focus on generative AI and agentic capabilities.
• Architect and implement LLM-based systems to enhance user interaction, financial data insights, and decision-making.
• Build new features and evolve existing ones, including a chatbot with RAG, platform insights, and financial data extraction tools.
• Ensure smooth integration with a microservices architecture and external data sources.
• Develop and maintain robust data pipelines for ingestion, processing, and schema evolution.
• Contribute to building a reference dataset and benchmarking suite to ensure quality and scalability.
• Collaborate with cross-functional teams to design modular architectures adaptable to emerging ML tools and technologies.
• Stay up to date with the latest in AI/ML, including generative models, embeddings, and context engineering methods (RAG, MCP, etc.).
• Mentor junior engineers, fostering innovation and knowledge sharing within the AI team.

Who You Are

• Proven experience designing and deploying production-grade AI/ML systems.
• Strong expertise in generative AI, LLMs, and agent-based systems.
• Solid programming skills in Python and experience building/deploying APIs (FastAPI or similar).
• Hands-on experience with multiple LLM providers (Gemini, Claude, GPT, etc.), with the ability to benchmark and select the best model.
• Practical experience with context engineering methods such as RAG and MCP, and the ability to implement them in production systems.
• Experience with AWS, Azure, or GCP and their AI services.
• Knowledge of data security, compliance, and safe AI operations.
• Strong problem-solving skills with a focus on scalability and performance optimization.
• Excellent communication skills for working with cross-functional teams and stakeholders.
• Fintech/financial data experience is a plus but not required.

Nice-to-Haves

• Experience building benchmarking frameworks and datasets.
• Exposure to multilingual NLP models.
• Familiarity with fintech platforms or data sources.