GenAI Field Application Engineer Intern
Beijing Tianjin Full-time Junior AI Engineering
At a glance
Junior AI Engineering role at Nxp. Beijing · full-time.
Pay not stated AI Engineering salary
RoleAI Engineering
SeniorityJunior
LocationBeijing
EmploymentFull-time
PostedSep 9, 2026 · 6w ago
Also hiring inTianjin
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Develop and roll out GenAI tools for engineering productivity, internal knowledge access, and business workflow automation
- Build knowledge assistants, AI agents, and document search systems for engineering, sales, and customer support teams
- Automate information gathering, report writing, knowledge extraction, and analysis using enterprise data
- Prototype technical knowledge search, customer visit summaries, project tracking, and task automation
- Test AI platforms, prompts, and agent designs, then document working methods for internal use
What you bring
- You are studying for a bachelor's or master's degree in computing, engineering, AI, data science, information systems, or a related discipline
- You can use Python and apply basic software development practices
- You have used at least one AI platform or framework, such as OpenAI API, Azure AI Services, or another listed option
- You bring strong analytical problem-solving, cross-team communication, and English reading and writing skills
Who this fits
This junior internship suits a student interested in applying GenAI and large language models to internal tools and workflows. You’ll work with engineering, field application engineering, and digital transformation teams in Beijing.
From the employer
Responsibilities
- Participate in the development and deployment of Generative AI use cases to improve engineering productivity, knowledge management, and business workflow automation.
- Design and implement AI-powered solutions using Microsoft Copilot, Copilot Studio, Glean, Vero, Power Automate, SharePoint and other enterprise AI platforms.
- Build and maintain internal knowledge assistants, AI agents, and document retrieval systems for engineering, sales, and customer support teams.
- Develop workflows for automated information collection, report generation, knowledge extraction, and data analysis from enterprise data sources.
- Create Proof-of-Concept (PoC) projects for AI-driven engineering use cases including technical knowledge search, customer visit report summarization, project tracking, and task automation.
- Evaluate and benchmark different AI tools, prompt engineering techniques, and agent architectures to improve solution quality and user experience.
- Collaborate with engineering, field application engineering (FAE), and digital transformation teams to identify and implement new GenAI opportunities.
- Document use cases, workflows, best practices, and technical implementation guides for internal adoption.
Requirements
- Master or Bachelor student in Computer Science, Software Engineering, Electronic Engineering, Artificial Intelligence, Data Science, Information Systems, or relevant disciplines.
- Strong interest in Generative AI, Large Language Models (LLM), AI Agents, and enterprise AI applications.
- Familiar with Python programming and basic software development practices.
- Familiar with one or more AI frameworks or platforms such as OpenAI API, Azure AI Services, Microsoft Copilot, Copilot Studio, LangChain, Semantic Kernel, or similar technologies.
- Understanding of Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, or knowledge management concepts is a plus.
- Familiar with Microsoft 365 ecosystem including SharePoint, Teams, Power Automate, Power Apps, or Power BI is a plus.
- Experience with web development, data visualization, workflow automation, or chatbot development is a plus.
- Strong analytical thinking and problem-solving skills.
- Good communication skills and teamwork for cross-functional and global collaboration.
- Good English reading and writing skills.
Preferred Qualifications
- Experience with AI agent development, chatbot implementation, or LLM-based applications.
- Experience with Glean, Vero, Microsoft Copilot, Copilot Studio, Power Platform, or similar enterprise AI tools.
- Experience with enterprise search, knowledge management systems, or document intelligence solutions.
- Contributions to open-source projects, hackathons, research projects, or AI-related publications are highly appreciated.