SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 184,000 - 299,812 / 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 own high-impact initiatives across Decisioning Studio, including agent setup, creative workflows, launch processes, and reporting systems that help marketers understand and trust AI-driven results. You'll build the full stack—from dashboard UI to backend APIs and services connecting Braze's platform to ML pipelines—while collaborating with Product, Design, and ML engineering teams to translate a fast-moving AI roadmap into intuitive, reliable software.
You will lead efforts in web application architecture to ensure scalability, maintainability, and performance; influence Braze's product strategy by providing technical insights; mentor engineers and foster a high-performance culture; and support customer success in implementing Braze's AI solutions.
You bring 7+ years of relevant experience with a proven track record of delivering impact. You work comfortably across the full stack, designing data models, APIs, and background jobs while owning product surfaces end-to-end. You are a strong frontend developer proficient in TypeScript and React (Vue experience is a plus) with a high bar for polished, intuitive UX and the testing discipline to keep it reliable. You have deep expertise in designing and maintaining scalable web application architectures and 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 people actually read. You explain complex systems to engineers, product partners, and stakeholders alike. You have a user-centric attitude, take pride in elegant and maintainable code, and are comfortable navigating large codebases with multiple stakeholders while driving consensus on technical decisions. Experience mentoring engineers and contributing to their technical development is essential.
Strongly preferred: experience developing UX for machine learning and data-intensive applications, building product surfaces on top of LLMs and agentic systems (embeddings, agent orchestration, evaluation), and proficiency in Python and/or Ruby on Rails.
