Senior AI Agent Engineer

Zendesk; York and North Yorkshire; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A cutting-edge tech company is seeking an experienced AI Agent Engineer to design and develop intelligent autonomous agents. The successful candidate will innovate at the forefront of AI technology, leveraging large language models to streamline operations and create systems that reason, plan, and execute complex tasks. This hybrid role offers flexibility, collaboration across teams, and opportunities to drive high-impact AI solutions.

Qualifications

• Strong expertise in Python, FastAPI, and cloud deployment.
• Experience with LLM-oriented system design for intelligent agents.
• Familiar with ML concepts like attention, embeddings, and transfer learning.

Responsibilities

• Design and develop autonomous AI agents using Python.
• Integrate AI solutions with enterprise systems and APIs.
• Optimize the performance and scalability of AI systems.

Skills

LLM‑Oriented System Design

Tool Integration & APIs

Retrieval‑Augmented Generation (RAG)

Performance Optimization

Programming & Tooling

Education

Ph.D. or Master’s degree in Computer Science, AI, Machine Learning, or NLP

Tools

Python

FastAPI

AWS

GCP

Azure

Job description

The Agentic Tribe is revolutionizing the chatbot and voice assistance landscape with Gen3, a cutting‑edge AI Agent system that pushes the boundaries of conversational AI. Gen3 is not your typical chatbot; it is goal‑oriented, dynamic, and truly conversational—capable of reasoning, planning, and adapting to user needs in real time.

About the Role

We are looking for a passionate and experienced AI Agent Engineer to innovate at the forefront of AI technology. In this role, you will design, develop, and deploy intelligent autonomous agents that leverage large language models to streamline operations. You will build the cognitive architecture for AI‑powered applications, creating systems that can reason, plan, and execute complex, multi‑step tasks while communicating technical concepts clearly to both technical and non‑technical stakeholders.

What You’ll Do (Responsibilities)

• Design and develop robust, stateful, and scalable AI agents using Python and modern agentic frameworks such as LangChain and 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 providers like OpenAI, Anthropic, and Google, analyzing strengths, weaknesses, and cost‑effectiveness for specific use cases.
• Drive the entire lifecycle of AI agent deployment—collaborate closely with product managers, ML scientists, and software engineers to understand user needs and deliver 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, and research findings to ensure knowledge sharing and maintainability across the team.

Core Technical Competencies

• LLM‑Oriented System Design: Multi‑step, tool‑using agents, prompt engineering, context management, and advanced reasoning patterns such as Chain‑of‑Thought and multi‑agent communication.
• Tool Integration & APIs: Securely integrate agents with external tools, databases, and APIs (OpenAI, Anthropic).
• Retrieval‑Augmented Generation (RAG): Build and optimize RAG pipelines with vector databases, advanced chunking, and hybrid search.
• Evaluation & Observability: Implement LLM evaluation frameworks and monitor latency, accuracy, and tool usage.
• Safety & Reliability: Guard against prompt injection and implement guardrails (Rebuff, Guardrails AI) and fallback strategies.
• Performance Optimization: Manage LLM token budgets and latency via smart model routing and caching (Redis).
• Planning & Reasoning: Design agents with long‑term memory and complex planning capabilities (ReAct, Tree‑of‑Thought).
• Programming & Tooling: Expertise in Python, FastAPI, LLM SDKs, and cloud deployment (AWS/GCP/Azure) with CI/CD for AI applications.

Bonus Points (Preferred Qualifications)

• Ph.D. or Master’s degree in Computer Science, AI, Machine Learning, or NLP.
• Deep understanding of foundational ML concepts such as attention, embeddings, and transfer learning.
• Experience translating academic research into production‑ready code.
• Familiarity with fine‑tuning techniques such as PEFT and LoRA.

The Interview Process

We are excited to learn more about you and want to be transparent about what you can expect from our interview process.

1. Initial Call with Talent Team – 15 minutes
2. Interview with one member of the Hiring Team – 45 minutes
3. Take‑home technical challenge
4. Technical interview with two of our developers to discuss your technical experience and answer questions – 1 hour
5. Final interview with 2 of the following: CTO or Engineering Manager/Director – 45 minutes

Hybrid Work Arrangement

This role is hybrid; you will attend our local office for part of the week while having flexibility to work remotely for the remainder of the week. The specific in‑office schedule will be determined by the hiring manager.

Equal Opportunity Statement

Zendesk is an equal‑opportunity employer and is committed to fostering diversity, equity, and inclusion. Applicants and employees are considered without regard to race, color, religion, national origin, age, sex, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability, military or veteran status, or any other characteristic protected by applicable law.