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Salary: USD 184,000 - 299,812 / annual
Braze is seeking a Staff Software Engineer to join the AI Decisioning Experience team in New York City. In this role, you will lead high-impact initiatives across Decisioning Studio, Braze's AI decisioning product line (reinforcement learning-based personalization), spanning both self-serve DS Go and managed DS Pro tiers. You will own critical workflows including agent setup, creative configuration, launch processes, reporting systems that help marketers understand and trust AI results, and backend services connecting the user experience to ML pipelines.
You will work across the full stack—designing data models, building APIs, developing background jobs, and owning product surfaces end-to-end. Your responsibilities include collaborating closely with Product, Design, and ML engineering teams to translate a fast-moving AI product roadmap into intuitive, reliable software. You will lead efforts in web application architecture to ensure scalability, maintainability, and performance. A key expectation is expertise in agentic development: AI coding agents should be your default workflow, and you should have a track record of dramatically above-baseline throughput without sacrificing code quality.
Beyond individual contribution, you will mentor engineers, provide technical guidance on their growth, and foster a high-performance engineering culture. You will influence Braze's product strategy by providing technical insights and driving innovation in user experience. You will also support teams implementing Braze's AI solutions to ensure customer success.
Required qualifications include 7+ years of relevant software engineering experience with a strong delivery track record. You must be a strong full-stack developer comfortable with TypeScript and React (Vue experience is a plus), with expertise in frontend development and a high bar for polished, intuitive UX. You need deep experience designing and maintaining scalable web application architectures, excellent written and verbal communication skills, and a user-centric mindset. Experience mentoring engineers 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.
