AI Software Engineer

CA-Ontario-Toronto · 3+ years experience · Full-time · Hybrid · Posted Oct 13, 2026

At a glance

Snowflake is looking for a Software Engineer for their growing Toronto engineering team to design, build, and ship AI-powered systems and services.
The role involves working on model inference, AI functions, retrieval systems, and intelligent application experiences on the Snowflake platform for enterprise customers worldwide.

Design, develop, and ship AI-powered features and services, working across model inference, AI functions, retrieval systems, and intelligent application experiences on the Snowflake platform.
Build production-quality infrastructure for AI workloads, including model serving, embedding pipelines, retrieval-augmented generation (RAG), and AI-driven automation.
Write clean, performant, and well-tested code in languages like Python, Java, C++, or Go, contributing to systems that operate at enterprise scale across Snowflake's multi-cloud infrastructure.
Collaborate with ML researchers, senior engineers, and product managers to translate AI research and product requirements into robust, scalable engineering solutions.
Contribute to system design by participating in design reviews, proposing architectural improvements, and helping shape the technical direction of AI services.
Own work end-to-end, from design and implementation through testing, deployment, monitoring, and operational health.
Stay current on AI/ML advancements by evaluating new techniques, models, and tools and assessing their applicability to Snowflake's platform and customer needs.
Contribute to a strong engineering culture through code reviews, documentation, knowledge sharing, and continuous improvement of team practices.

3+ years of software engineering experience building production systems, with a strong foundation in computer science fundamentals (data structures, algorithms, distributed systems).
Experience with AI/ML systems, including working on model serving, inference pipelines, LLM integration, embedding systems, or AI-powered application features in a production environment.
Proficiency in one or more of: Python, Java, C++, or Go.
Experience building distributed systems or cloud-native services with an understanding of scale, reliability, and performance in a multi-cloud environment.
Strong problem-solving skills and the ability to break down ambiguous problems into clear engineering tasks.
Collaborative mindset to work effectively with engineers, researchers, and product managers and communicate ideas clearly.
Ownership mentality to take responsibility for work from design through production and care about quality, reliability, and operational excellence.

Experience with LLM inference, fine-tuning, RAG architectures, or vector search at production scale.
Familiarity with ML frameworks such as PyTorch, TensorFlow, or similar.
Experience with cloud infrastructure (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
Background in data platforms, data warehousing, or SQL-based systems.
Experience with CI/CD pipelines, automated testing, and production monitoring/observability.
Contributions to open-source AI/ML projects or published research in AI/ML.