AI Engineer

Infosys is a global leader in next-generation digital services and consulting. Over 320,000 of our people work to amplify human potential and create the next opportunity for people, businesses and communities. We enable clients in 59 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer clients, as they navigate their digital transformation powered by cloud and AI. We enable them with an AI-first core, empower the business with agile digital at scale and drive continuous improvement with always-on learning through the transfer of digital skills, expertise, and ideas from our innovation ecosystem. We are deeply committed to being a well-governed, environmentally sustainable organization where diverse talent thrives in an inclusive workplace.

Visit www.infosys.com to see how Infosys (NYSE: INFY) can help you navigate your next.

Recognized as a Top Employer🎉 across China — contributing to our global certification. As an AI first organization, we empower our people to work on next generation technologies, continuously learn, and create impact at scale—supported by a culture rooted in care, inclusion, and excellence.

▶️Join Infosys and be part of a culture that’s not just promised—it’s certified. #Top Employer2026 #Thrive AtInfosys.

We promote a flexible, outcome-driven way of working. Subject to business and client requirements, certain roles may benefit from flexible working hours. The specific arrangement is jointly assessed by the company and the team, based on role level and business context.

岗位职责

1. 负责开发基于AI/GenAI的核心组件，支持逆向工程相关业务流程
2. 搭建并优化RAG（检索增强生成）系统，包括向量检索、Embedding处理等
3. 设计与开发知识型AI Agent，支持企业知识问答与智能决策场景
4. 参与构建知识图谱 / 文档知识建模体系，提升知识结构化能力
5. 支持AI辅助代码生成能力建设（以Java技术栈为主）
6. 参与AI系统的部署、测试及性能优化，确保生产环境稳定运行
   任职要求
7. 大专及以上学历，4年及以上AI/ML项目实践经验
8. 具备的Python开发能力，有完整的RAG项目经验（包含embedding、检索、向量数据库应用）
9. 理解大语言模型（LLM）原理、Prompt工程及API集成方式
10. 具备AI/ML解决方案在生产环境的落地经验（Mandatory）
11. 英文口语流利

• In addition to compensation aligned with your role, you’ll have access to a wide range of benefits that support your health, career growth, and overall well-being
• Social Insurance & Housing Fund
• Supplemental Commercial Insurance
• Paid Leaves: Annual / Eldercare / Childcare Leave
• Work from Home (Based on business arrangement)
• Employee Assistance Program (EAP)

Our recruitment and selection process is designed to create the best match for both you and Infosys. Depending on the role, it may include an initial screening, technical or functional interviews, and conversations focused on cultural alignment and shared values. We are committed to making the experience transparent, respectful, and engaging at every step.

Hear from our recruiter on their experience working with Infosys as an Employer
At Infosys, we recognize that everyone has individual requirements. If you are a person with disability, illness, or injury and require adjustments to the recruitment and selection process, please contact our Recruitment team for adjustment either via the following email Infy_REC_Helpdesk@infosys.com or call 1-866-472-0935. Alternatively, you can include your preferred method of communication in email, and someone will be in touch.

Please note in order to protect the interest of all parties involved in the recruitment process, Infosys does not accept any unsolicited resumes from third-party vendors. In the absence of a signed agreement, any submission will be deemed as non-binding and Infosys explicitly reserves the right to pursue and hire the submitted profile. All recruitment activity must be coordinated through the Talent Acquisition department.

“All aspects of employment at Infosys are based on merit, competence and performance. We are committed to embracing diversity and creating an inclusive environment for all employees. Infosys is proud to be an equal opportunity employer.”

• Primary skills:Technology->Machine Learning->Tensor Flow

Education: Bachelor Of Computer Science

Preferred skills: Technology->Machine Learning->Tensor Flow