AI Software Engineer
SnowflakeAbout the Role
At Snowflake, we are powering the era of the agentic enterprise. We seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don't just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact.
Snowflake is building the most powerful AI Data Cloud in the world — and Canada is a critical part of that mission. Our AI/ML engineering teams are delivering the intelligence layer that powers Cortex AI, large language model inference, AI functions, intelligent search, and the next generation of AI-powered experiences on the Snowflake platform.
We're looking for a Software Engineer — AI to join our growing Toronto engineering team. You'll design, build, and ship AI-powered systems and services that are used by thousands of organizations worldwide.
Responsibilities
- 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 — participate in design reviews, propose architectural improvements, and help shape the technical direction of AI services
- Own your work end-to-end — from design and implementation through testing, deployment, monitoring, and operational health
- Stay current on AI/ML advancements — evaluate new techniques, models, and tools and assess 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
Requirements
Required
- 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 — you've worked 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 — you understand the challenges 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 — you work effectively with engineers, researchers, and product managers and communicate your ideas clearly
- Ownership mentality — you take responsibility for your work from design through production and care about quality, reliability, and operational excellence
Preferred
- 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
Snowflake Values
- Get It Done — You ship working software. You move fast, iterate, and deliver results — not just prototypes.
- Own It — You take end-to-end responsibility for your code, your systems, and your outcomes. If something breaks, you fix it.
- Make Each Other the Best — You contribute to a culture of learning through thoughtful code reviews, knowledge sharing, and helping teammates grow.
- Think Big — You don't just solve today's problem. You think about how AI at Snowflake should work at 10x scale and build with that future in mind.
Compensation
Snowflake is committed to pay equity and transparency. The compensation ranges below are for the Canada market. Actual compensation will be determined based on factors including relevant experience, skills, and internal equity.
- Base Salary: $146,000 – $219,000 CAD
- Annual Bonus Target: 10% of base salary
- Total Target Compensation: $160,600 – $240,900 CAD
- Equity (RSUs): $170,000 – $500,000 USD
In addition, this role is eligible for a comprehensive benefits package including extended health, dental, vision, RRSP, ESPP, generous paid time off, parental leave, and more.
Why Snowflake Toronto?
- AI at enterprise scale — Cortex AI powers intelligent features for thousands of organizations; your code ships to production and impacts real customers
- Work at the frontier — LLM inference, AI functions, intelligent search, agentic workflows — this team is building the AI platform layer of the data cloud
- Toronto's growing engineering hub — join a rapidly expanding office with strong local engineering leadership and team culture
- Unmatched data advantage — Snowflake sits on one of the largest concentrations of enterprise data in the world, giving AI products a unique moat
- World-class colleagues — work alongside engineers from Google, Meta, Amazon, Microsoft, and leading AI research labs
- Competitive compensation and meaningful equity — including RSUs that give you real ownership in Snowflake's growth
About Snowflake
<cite index="12-3,12-4">Snowflake develops and sells a cloud-based data platform known as the Data Cloud. The platform allows organizations to unify data warehousing, data lakes, data engineering, and data sharing into a single service.</cite> <cite index="12-5">Snowflake runs on public cloud infrastructure such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), and separates compute from storage for scalable, on-demand analytics.</cite></description> <parameter name="industry">Cloud Data Platform / Software
Interested in this role?
Apply now to join Snowflake.