About the role

AI Software Engineer building model-serving, RAG, and AI-powered services for Snowflake’s enterprise data cloud. Toronto-based hybrid role shipping scalable systems used by organizations worldwide.

Responsibilities

Design, develop, and ship AI-powered features and services across model inference, AI functions, retrieval systems, and intelligent application experiences
Build production-quality infrastructure for AI workloads, including model serving, embedding pipelines, retrieval-augmented generation, and AI-driven automation
Write clean, performant, and well-tested code in Python, Java, C++, or Go
Contribute to systems operating 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 scalable engineering solutions
Participate in design reviews and propose architectural improvements
Help shape the technical direction of AI services
Own work end-to-end from design and implementation through testing, deployment, monitoring, and operational health
Evaluate new AI/ML techniques, models, and tools for applicability to Snowflake's platform and customer needs
Contribute through code reviews, documentation, knowledge sharing, and continuous improvement of team practices

3+ years of software engineering experience building production systems
Strong foundation in computer science fundamentals, including data structures, algorithms, and distributed systems
Experience with AI/ML systems in a production environment, including model serving, inference pipelines, LLM integration, embedding systems, or AI-powered application features
Proficiency in one or more of Python, Java, C++, or Go
Experience building distributed systems or cloud-native services
Understanding of scale, reliability, and performance in a multi-cloud environment
Strong problem-solving skills
Ability to break down ambiguous problems into clear engineering tasks
Ability to work effectively with engineers, researchers, and product managers
Clear communication of ideas
Ownership of work from design through production
Care about quality, reliability, and operational excellence
Experience with LLM inference, fine-tuning, RAG architectures, or vector search at production scale preferred
Familiarity with ML frameworks such as PyTorch or TensorFlow preferred
Experience with AWS, Azure, or GCP and Docker or Kubernetes preferred
Background in data platforms, data warehousing, or SQL-based systems preferred
Experience with CI/CD pipelines, automated testing, and production monitoring/observability preferred
Contributions to open-source AI/ML projects or published research in AI/ML preferred