Fullstack Engineer (AI)

TL;DR

Fullstack Engineer (AI): Architecting and building server-side systems and LLM orchestration layers to power dynamic user experiences with an accent on API design, data pipelines, and inference infrastructure. Focus on integrating large language models into production-grade services, ensuring reliability, security, and performance at scale.

Location: Toronto

Salary: CA$172,000 - CA$258,000

Company

Stripe is a financial infrastructure platform for businesses, enabling millions of companies to accept payments and grow their revenue globally.

What you will do

• Architect and build server-side systems and LLM orchestration layers for intelligent user experiences.
• Design APIs, data pipelines, and inference infrastructure for interactive tools.
• Manage prompt pipelines, model routing, fallback logic, and output guardrails.
• Ensure reliability, security, and responsible AI practices including PII handling and rate limiting.
• Collaborate across design and engineering teams to create new site capabilities.
• Implement feedback mechanisms for continuous improvement of content and product offerings.

Requirements

• 5+ years of backend development experience building APIs and services.
• Experience building and operating distributed backend systems.
• Familiarity with LLM APIs and concepts like prompt engineering, token management, and RAG.
• Experience writing clear, elegant code in a team environment.
• Excellent verbal and written communication skills.
• Must be based in or able to work from Toronto.

Nice to have

• Proficiency with React, focusing on interactions, animation, and performance.
• Experience with data pipeline orchestration tools like Airflow, Dagster, or Temporal.
• Experience with prompt versioning, A/B testing model outputs, and building model gateways.
• Ability to stitch different services and processes together.

Culture & Benefits

• Opportunity to work on high-impact global financial infrastructure.
• Collaborative environment with technically sophisticated engineers.
• Focus on user-first product development and growth hacking.
• Commitment to building reliable, performant, and safe production-grade AI features.