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Salary: CAD 184,000 - 348,000 / annual
Braze is seeking a Staff Software Engineer to join the AI Decisioning Experience team and lead the evolution of its reinforcement learning-based personalization platform. In this role, you will drive high-impact initiatives across Decisioning Studio (both self-serve DS Go and managed DS Pro tiers), spanning agent setup, creative workflows, launch processes, reporting systems, and backend services that connect the user experience to ML pipelines.
You will own the full technical stack—from React/TypeScript frontend dashboards to backend APIs, data models, and background jobs—while collaborating closely with Product, Design, and ML engineering teams to translate a fast-moving AI roadmap into intuitive, reliable software. A key part of this role is leading web application architecture efforts to ensure scalability, maintainability, and performance across the platform, as well as influencing Braze's product strategy through technical insights and innovation in user experience.
Beyond individual contribution, you will mentor engineers, guide their technical growth, and foster a high-performance engineering culture. You will also support teams implementing Braze's AI solutions to ensure customer success and effective cross-functional collaboration.
You bring 7+ years of relevant software engineering experience with a proven track record of delivering impact. You are a full-stack engineer comfortable designing and maintaining scalable web application architectures, with strong frontend expertise in TypeScript and React (Vue experience is a plus). You are an expert practitioner of agentic development—AI coding agents are your default workflow, you build reusable skills and automation that raise team velocity, and you have a track record of dramatically above-baseline throughput without sacrificing quality.
You communicate with clarity in writing and in person, producing design docs and technical proposals that stakeholders actually read. You have a user-centric attitude, take pride in elegant and maintainable code, and are comfortable navigating large codebases with multiple stakeholders to drive consensus on technical decisions. Experience developing UX for machine learning and data-intensive applications, building product surfaces on top of LLMs and agentic systems, and familiarity with Python or Ruby on Rails are strongly preferred.
