Braze currently has 24 active AI-related job listings. The majority of these roles, 71%, are focused on agents, with application roles making up another 17%. Engineering is the most frequent function for these positions, followed by Product. Hiring is primarily concentrated in the United States, with additional roles in Brazil and the United Kingdom. Frequent tech tags include agent_orchestration, tool_use, and rag, suggesting a focus on developing and deploying AI agents that can interact with external tools and information.
Enterprise · Marketing automation
Currently tracking 15 active AI roles, up 10% versus the prior 4 weeks. Primary focus: Post-train · Engineering. Salary range $98k–$165k (avg $138k).
Braze currently has 33 active AI-related roles in our index. The most common open titles are: Director, CX Business Systems (5), Applied AI Architect (4), Senior Lead Systems Engineer, AI & Automation (4), Senior Technical Product Manager, Content Platforms (Localization) (4), Forward Deployed AI Accelerator (3). Most positions are in Engineering and Product.
Braze's active AI hiring is concentrated in: agents (76%), application (18%), post-training (6%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Braze is hiring AI talent in: United States (24 roles), Brazil (4 roles), Japan (2 roles), Canada (2 roles).
Job postings at Braze most frequently mention: Reinforcement Learning (RL), Technical Leadership, System Design, Streaming Data, Robotics.
In the past 30 days, Braze has posted 17 new AI-related roles. That is a +31% change versus the prior 30 days (13 → 17).
| Title | Stage | AI score |
|---|---|---|
| Senior Software Engineer I, ML Senior Software Engineer to design, improve, and scale Braze's self-learning (reinforcement learning) AI platform, focusing on production AI pipelines and data architecture. | ServeData | 7 |
| AI Platform Engineer II The AI Platform Engineer II will build and scale BrazeAI Decisioning Studio, a reinforcement learning platform for personalized customer engagement. This role involves working with cloud-native infrastructure, data-intensive systems, and production machine learning, focusing on building and maintaining critical services, implementing scalable cloud solutions, troubleshooting production issues, and collaborating with data scientists and ML engineers. | Serve |
| 7 |