Job Description

Senior AI Agent Engineer (Machine Learning) at Zendesk

About The Agentic Tribe:
The Agentic Tribe is revolutionizing the chatbot and voice assistance landscape with Gen3, a cutting-edge AI Agent system that is goal-oriented, dynamic, and truly conversational, capable of reasoning, planning, and adapting to user needs in real-time. By leveraging a multi-agent architecture and advanced language models, Gen3 delivers personalized experiences and handles complex tasks and off-script inquiries.

About The Role

We are seeking a passionate and experienced AI Agent Engineer to join our team. In this role, you will innovate at the forefront of AI technology, designing, developing, and deploying intelligent, autonomous agents that leverage Large Language Models (LLMs) to streamline operations. You will be a key player in building the cognitive architecture for our AI-powered applications, creating systems that can reason, plan, and execute complex, multi-step tasks. You’ll effectively communicate complex technical concepts to both technical and non-technical stakeholders, including those outside your immediate team.

What You Will Do (Responsibilities)

• Design and develop robust, stateful, and scalable AI agents using Python and modern agent frameworks (e.g., LangChain, LlamaIndex).
• Integrate AI agent solutions with existing enterprise systems, databases, and third-party APIs to create seamless, end-to-end workflows.
• Evaluate and select appropriate foundation models and services from third-party providers (e.g., OpenAI, Anthropic, Google), analyzing strengths, weaknesses, and cost-effectiveness for specific use cases.
• Drive the entire lifecycle of AI Agent deployment — collaborate with product managers, ML scientists, and software engineers to understand user needs and deliver effective, high-impact agent solutions.
• Troubleshoot, debug, and optimize complex AI systems to ensure optimal performance, reliability, and scalability in production environments.
• Establish and improve platforms for evaluating AI agent performance, defining key metrics to measure success and guide iteration.
• Document development processes, architectural decisions, code, and research findings to ensure knowledge sharing and maintainability across the team.

Core Technical Competencies

• LLM-Oriented System Design: Designing multi-step, tool-using agents (LangChain, Autogen). Deep understanding of prompt engineering, context management, and LLM behavior quirks. Implementing advanced reasoning patterns like Chain-of-Thought and multi-agent communication.
• Tool Integration & APIs: Integrating agents with external tools, databases, and APIs (OpenAI, Anthropic) in secure execution environments.
• Retrieval-Augmented Generation (RAG): Building and optimizing RAG pipelines with vector databases, chunking, and hybrid search.
• Evaluation & Observability: Implementing LLM evaluation frameworks and monitoring for latency, accuracy, and tool usage.
• Safety & Reliability: Defending against prompt injection and implementing guardrails and fallback strategies.
• Performance Optimization: Managing LLM token budgets and latency through model routing and caching (Redis).
• Planning & Reasoning: Designing agents with long-term memory and complex planning capabilities (ReAct, Tree-of-Thought).
• Programming & Tooling: Proficient in Python, FastAPI, and LLM SDKs; experience with cloud deployment (AWS/GCP/Azure) and CI/CD for AI applications.

Bonus Points (Preferred Qualifications)

• Ph.D / Masters in a relevant field (e.g., Computer Science, AI, Machine Learning, NLP).
• Deep understanding of foundational ML concepts (attention, embeddings, transfer learning).
• Experience translating academic research into production-ready code.
• Familiarity with fine-tuning techniques (e.g., PEFT, LoRA).

The Interview Process

We are excited to learn more about you and transparent about what to expect from our interview process:

• Initial Call with Talent Team – 15 mins
• Interview with one member of the Hiring Team – 45 minutes
• Take-home technical challenge
• A technical interview with two of our developers to discuss your technical experience – 1 hour
• Final interview with 2 of the following: CTO or Engineering Manager/Director – 45 minutes

About Zendesk

Zendesk builds software for better customer relationships. It empowers organizations to improve customer engagement and better understand their customers. Zendesk products are easy to use and implement, giving organizations the flexibility to move quickly, focus on innovation, and scale with growth.

Zendesk is an equal opportunity employer with ongoing efforts to foster diversity and inclusion. We are committed to a hybrid work model with options to work remotely part of the week and in-office at various locations worldwide.

We may collect your personal data for recruiting and related purposes. Zendesk’s Candidate Privacy Notice explains what information is processed and your rights.

Seniority level

• Mid-Senior level

Employment type

• Full-time

Job function

• Sales and Business Development
• Industries: Software Development