Senior AI Engineer

Role overview

Design, build, and operate production AI and machine learning systems as part of a cross-functional engineering team. The role covers the full delivery path—from models, data pipelines, and training workflows to deployment and ongoing reliability—and includes contributing to architecture and technical decisions as systems evolve.

Responsibilities - Implement and deploy AI/ML models, supporting data pipelines, training, and performance improvements. - Maintain production systems by monitoring for drift, investigating issues, and improving reliability and scalability. - Work with product, engineering, and data colleagues to connect AI capabilities to user and business needs. - Explain model behavior, constraints, and technical tradeoffs to people outside the engineering team. - Participate in design discussions and code reviews, contribute to architecture choices, and support less experienced engineers. - Use AI-assisted coding tools as part of the development workflow.

Requirements - At least four years of professional software engineering experience, including two or more years building AI/ML systems for production and hands-on generative AI development. - Strong software engineering skills in Python or a comparable language. - Experience designing and shipping agentic systems, and using AI frameworks and orchestration tools. - Familiarity with model evaluation and observability for LLM applications. - Understanding of AI safety and responsible AI principles. - Cloud platform experience; practical knowledge of AWS and its generative AI services is preferred. - Sound judgment, clear communication, and the ability to take work from ambiguous problem to production delivery.

Benefits and work setup

The role involves collaboration with North American clients and experienced engineering teams. Specialized cloud training and access to emerging cloud capabilities are described as part of the professional development environment.