Zendesk has 37 active AI-related job listings, with a significant focus on roles related to agents, accounting for 46% of their openings. Engineering is the most represented function, with 28 positions. The company is actively hiring in Portugal and Poland. Technical tags frequently appearing include model_serving, llm_observability, and agent_orchestration, suggesting a focus on deploying and managing AI models for customer service applications. Over the last 30 days, Zendesk has added 35 new AI roles, representing a 67% increase compared to the previous 30-day period.
Currently tracking 18 active AI roles, down 73% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $158k–$374k (avg $261k).
Zendesk currently has 29 active AI-related roles in our index. The most common open titles are: Staff Software Engineer (3), Senior Product Manager (2), Staff Machine Learning Engineer (2), AI Agent Abuse Prevention Engineer, AI Services Consultant II. Most positions are in Engineering and Product.
Zendesk's active AI hiring is concentrated in: agents (52%), application (21%), post-training (10%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Zendesk is hiring AI talent in: Portugal (12 roles), Poland (6 roles), United States (5 roles), Ireland (3 roles).
Job postings at Zendesk most frequently reference: llm observability, agent orchestration, model serving, rag, guardrails.
In the past 30 days, Zendesk has posted 17 new AI-related roles. That is a -45% change versus the prior 30 days (31 → 17).
| Title | Stage | AI score |
|---|---|---|
| Senior Machine Learning Engineer (Hybrid - Austin or SF) Senior Machine Learning Engineer to drive the development and deployment of advanced ML and AI solutions, particularly LLMs and deep learning. Responsibilities include architecting and scaling ML systems, ensuring enterprise-grade performance, reliability, and compliance, and driving MLOps best practices. The role requires strong programming skills, experience with data pipelines and deployment tools, and the ability to translate business needs into analytical solutions. | ServePost-train | 7 |