AI Agent Engineer (Machine Learning Engineer)

Zendesk; City Of London; On-site; GBP 55,000 - 75,000; Full time

Job summary

A leading technology company in London is seeking an AI Agent Engineer to innovate in AI technology, focusing on developing intelligent agents leveraging Large Language Models. You'll design robust AI agents, troubleshoot systems, and collaborate with teams to streamline operations. Ideal candidates will have strong Python skills and a background in AI. This role supports career growth in an inclusive environment.

Qualifications

• Familiarity with multi-step, tool-using agents.
• Basic understanding of prompt engineering and LLM behavior.
• Experience in integrating agents with external tools and APIs.

Responsibilities

• Design and develop AI agents using Python and frameworks.
• Evaluate and select appropriate models and services.
• Troubleshoot and debug AI systems for optimal performance.

Skills

Python

LLM system design

Tool Integration & APIs

Retrieval-Augmented Generation

Performance Optimization

Education

Bachelor's or Master's in Computer Science or related field

Job description

The Agentic Tribe is revolutionizing the chatbot and voice assistance landscape with Gen3, a cutting-edge AI Agent system that's pushing the boundaries of conversational AI. Gen3 isn't your typical chatbot; it's a goal-oriented, dynamic, and truly conversational system 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 and engaging user experiences, moving beyond scripted interactions to handle complex tasks and "off-script" inquiries with ease.

About the Role:

We're seeking a passionate AI Agent Engineer to join our team. In this role, you'll contribute to innovating at the forefront of AI technology, focusing on developing and refining intelligent, autonomous agents that leverage Large Language Models (LLMs) to streamline operations. You'll be a key player in implementing and improving the cognitive architecture for our AI-powered applications, creating systems that can reason, plan, and execute complex, multi-step tasks. You'll primarily focus on defined project scopes and tasks, working under the guidance of more senior team members.

What You'll Do (Responsibilities):

• Contribute to the design and development of robust, stateful, and scalable AI agents using Python and modern agentic frameworks (e.g., LangChain, LlamaIndex).
• Support the evaluation and selection of appropriate foundation models and services from third-party providers (e.g., OpenAI, Anthropic, Google), contributing to the analysis of their strengths, weaknesses, and cost-effectiveness for specific use cases.
• Participate in the lifecycle of AI Agent deployment—collaborate closely with your immediate team, including product managers and software engineers, to understand user needs for the features you're building.
• Troubleshoot and debug AI systems to ensure optimal performance and reliability in production environments for assigned components.
• Document development processes, code, and findings to ensure knowledge sharing and maintainability within the team.

Core Technical Competencies:

• Familiarity with LLM-Oriented System Design: Understanding of multi-step, tool-using agents (e.g., LangChain, Autogen). Basic understanding of prompt engineering, context management, and LLM behavior (e.g., hallucinations).
• Tool Integration & APIs: Ability to integrate agents with external tools, databases, and APIs (e.g., OpenAI, Anthropic) in secure execution environments.
• Retrieval-Augmented Generation (RAG): Understanding of RAG pipelines with vector databases.
• Evaluation & Observability: Basic understanding of LLM evaluation frameworks and monitoring for latency and accuracy.
• Safety & Reliability: Awareness of prompt injection and basic concepts of implementing guardrails and fallback strategies.
• Performance Optimization: Basic understanding of managing LLM token budgets and latency.
• Planning & Reasoning: Familiarity with concepts of agents with long-term memory and planning capabilities.
• Programming & Tooling: Proficient in Python (Fast API) and LLM SDKs;

Bonus Points (Preferred Qualifications):

• Bachelor's or Master's in a relevant field (e.g., Computer Science, AI, Machine Learning, NLP).
• Understanding of foundational ML concepts (attention, embeddings, transfer learning).

The Interview Process:

We are excited to learn more about you, so we want to be transparent about what you can expect from our interview process:

1. Initial Call with Talent Team - 15 mins
2. Interview with one member of the Hiring Team - 45 minutes
3. Take-home technical challenge
4. A technical interview with two of our developers to talk more in-depth about your technical experience and answer any questions you might have - 1 hour
5. Final interview with 2 of the following: CTO or Engineering Manager/Director - 45 minutes

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. They give organizations the flexibility to move quickly, focus on innovation, and scale with their growth.

Zendesk is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Zendesk are considered without regard to race, color, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.

Zendesk endeavors to make reasonable accommodations for applicants with disabilities and disabled veterans pursuant to applicable federal and state law. If you are an individual with a disability and require a reasonable accommodation to submit this application, complete any pre-employment testing, or otherwise participate in the employee selection process, please send an e-mail to [e-mail] with your specific accommodation request.