Braze
Enterprise · Marketing automation
Braze currently has 26 active job listings related to AI. The majority of these roles are focused on the application stage, representing 42% of the openings, followed by post-training roles at 38%. Engineering is the most active function, with 15 listings, and the United States is the primary hiring country with 10 positions. The company is frequently seeking candidates with experience in model serving, fine-tuning, and recommender systems. In the last 30 days, Braze has posted 5 new AI roles, a 150% increase compared to the previous 30-day period.
Currently tracking 15 active AI roles, down 25% versus the prior 4 weeks. Primary focus: Post-train · Engineering. Salary range $98k–$165k (avg $138k).
Enterprise · Marketing automation
Braze currently has 23 active AI-related roles in our index. The most common open titles are: Engagement Manager II (8), Forward-Deployed Data Scientist II (7), Forward Deployed Data Scientist, AI Deployment, Data Scientist, AI Deployment, Forward-Deployed Data Scientist. Most positions are in Engineering and Product.
Braze's active AI hiring is concentrated in: application (43%), post-training (39%), agents (13%). 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 (10 roles), Brazil (4 roles), Canada (3 roles), Romania (2 roles).
Job postings at Braze most frequently reference: model serving, fine tuning, rl post training, recommender systems, agent orchestration.
In the past 30 days, Braze has posted 3 new AI-related roles. That is a -50% change versus the prior 30 days (6 → 3).
| Title | Stage | AI score |
|---|---|---|
| Forward-Deployed Data Scientist II This role focuses on designing and building end-to-end machine learning solutions, specifically RL use cases, for customer engagement personalization. The individual will own the full ML pipeline from data transformation to model training and activation, drive customer success through technical guidance, and contribute to extending product capabilities and shaping AI product strategy. The role involves partnering with the product team to advance reinforcement learning algorithms and bring customer-facing insights to the product roadmap. | AgentData | 7 |
| Forward-Deployed Data Scientist II This role focuses on designing and building end-to-end machine learning solutions, specifically RL use cases, for customer engagement personalization. The individual will own the full ML pipeline from data transformation to model training and activation, drive customer success through technical guidance, and contribute to extending product capabilities and shaping AI product strategy. The role involves partnering with the product team to advance reinforcement learning algorithms and bring customer-facing insights to the product roadmap. |
| AgentData |
| 7 |