Zendesk
Enterprise · Customer support
- HQ
- San Francisco, US
- Founded
- 2007
- Size
- 3,000+
- Website
- zendesk.com
Enterprise · Customer support
Currently tracking 20 active AI roles, up 72% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $158k–$374k (avg $261k).
| Title | Stage | AI score |
|---|---|---|
| Senior Staff Machine Learning Engineer Senior Staff Machine Learning Engineer at Zendesk to lead end-to-end design, development, and deployment of novel ML/LLM models and algorithms for customer service. The role involves pioneering initiatives like multilingual analysis, conversational AI agents, and agent-assist solutions, defining experimentation standards, and bridging research with production systems. Responsibilities include mentoring, advising leadership on AI strategy, and representing Zendesk externally. Key challenges involve agentic operations, automation of customer service interactions, large-scale A/B testing, leveraging RAG and fine-tuning for conversational AI, operationalizing LLMs, and incorporating emerging AI advancements. | AgentPost-train | 9 |
| Staff Software Engineer Staff Software Engineer focused on Engineering Productivity Test team, building AI-powered tooling and services to improve software testing, validation, and release processes for Zendesk engineers. The role involves owning core testing services, creating automation, and partnering with product teams to enhance developer experience and quality at scale. |
| Ship |
| 5 |
| Manager, AI Success Strategist, Customer Success This role focuses on customer success and strategic roadmap delivery for AI solutions within an enterprise context. The Manager, AI Success Strategist will own the end-to-end AI roadmap for key customers, translating product capabilities into business strategies, defining long-term AI vision, and driving adoption and operational excellence. The role requires strong project management, product and technical knowledge, business acumen, and the ability to influence executive stakeholders. While the role involves advising on AI strategy and ensuring ethical practices, it is primarily focused on customer adoption and business impact of existing AI products, rather than core AI/ML development or research. | — | 5 |