AI Agent Delivery Engineer

Job Responsibilities The core responsibility of an AI Agent Delivery Engineer is to drive the implementation of AI Agent technology in practical business scenarios, including: Analyzing customer requirements and designing AI Agent solutions tailored to business scenarios; Deploying Agent systems, integrating with customers' existing systems (such as CRM, databases), and resolving technical issues during integration; Configuring Agent workflows, decision-making logic, and exception handling rules; Conducting testing and acceptance, and optimizing based on feedback to ensure Agent functions meet standards; Training customers on usage and providing operation documents; Continuously monitoring operating status and iteratively optimizing in response to business changes. In short, this role needs to bridge technology and business, enabling AI agents to truly create value for customers. Job Requirements Education A bachelor's degree or higher, with priority given to majors such as Computer Science and Technology, Software Engineering, etc.; those with rich experience in Agent development or outstanding achievements can be considered with an associate degree. Fresh graduates should have good grades in computer-related courses; previous graduates need at least 1 year of relevant development experience. General Abilities Master basic computer concepts and the full software development process, understand the development framework and operation mechanism of AI Agent, and be able to independently develop and debug simple modules. Familiar with large models such as ChatGPT and Gemini; priority will be given to those with experience in using agent studios like cozes and N8N. Possess clear logic, be able to analyze and solve development problems, extract business requirements and convert them into technical solutions, and put forward optimization suggestions. Have a team spirit, be able to communicate efficiently with products, testing and other teams to ensure project progress and quality. Professional Skills Master Python syntax, data structures and common algorithms, be familiar with libraries such as NumPy and TensorFlow, have experience in network programming and API development, be able to realize system integration, and be proficient in using debugging and testing tools such as pdb and unittest. Fluent in English reading and writing, able to read English technical documents; have certain listening and speaking skills, and be able to participate in communication with international teams. Interested in the AI field, paying attention to technical trends, understanding basic concepts of machine learning and the principles of large models; priority will be given to those with practical experience in AI projects. Other Qualities Strong learning ability and self-drive, able to quickly master new knowledge; enthusiastic and responsible for work, able to deliver high-quality results on time; have innovative awareness, and be able to put forward plans to improve agent performance and user experience.

Location: Mexico City, Mexico, MX

Posted Date: 8/3/2025