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Zendesk is seeking an AI Product Consultant & Pilot Implementation (Pre-Sales) to lead end-to-end pilot engagements that prove the value of Zendesk AI through technical configuration, integration, and validation against success metrics. The role sits at the intersection of technology and strategy in the pre-sales cycle, building and implementing pilots with the latest AI tools while ensuring they address strategic business outcomes and accelerate sales cycles. Responsibilities include owning pilot discovery, scoping and delivery; partnering with the account team; driving readiness; configuring AI features and integrations; coordinating Professional Services support; interfacing with Product to address gaps; designing testing and QA for AI agents and Copilot; managing stakeholder relations; evaluating pilot performance against metrics; and maintaining handoff documentation while staying a product expert on Zendesk’s AI offerings. Required qualifications include a startup mindset, strong Zendesk product knowledge, consultancy experience, high technical aptitude with basic coding, project and relationship management, proactive outcome-driven attitude, excellent communication and change-management skills, and a track record of accelerating adoption; success metrics cover pilot-to-deal conversion, automation/augmentation of tickets, stakeholder satisfaction, time-to-value, risk management, asset reusability, knowledge transfer, and innovation contributions. Zendesk offers a flexible hybrid work model with optional weekly in-office collaboration, emphasizes inclusivity and diversity, notes that AI may be used to screen applicants, and provides accommodations for applicants with disabilities with a dedicated contact for requests.

The posting is for an AI Agent Engineer at Zendesk, highlighting Gen3—a cutting-edge, goal-oriented AI agent system that uses multi-agent architectures and LLMs to reason, plan, and adapt in real time. The role centers on designing, developing, and deploying autonomous agents that leverage LLMs to streamline operations and handle complex, multi-step tasks, while effectively communicating technical concepts to technical and non-technical stakeholders. Responsibilities include building robust, stateful AI agents with Python and frameworks like LangChain and LlamaIndex; integrating with enterprise systems and APIs; evaluating foundation models; leading deployment lifecycles with cross-functional teams; troubleshooting and documenting processes. Core competencies include LLM-oriented system design; tool integration and APIs; retrieval-augmented generation; evaluation and observability; safety and reliability; performance optimization; planning and reasoning; and proficiency in Python, FastAPI, cloud deployment, and CI/CD, with bonuses for advanced degrees, ML fundamentals, productionizing research, and fine-tuning methods. The interview process is multi-stage, and Zendesk emphasizes hybrid work, equal opportunity, diversity and inclusion, and candidate privacy, with mentions of AI-based screening and accommodations.