From Student to Influential Backend Engineer: My Journey with AI, Large‑Model Systems, and Technical Growth at JD

In an era where each technological leap reshapes work, the author, a JD 2023 campus recruit, shares a personal narrative of evolving from a directionless student to an influential technical explorer and practitioner, while reflecting on the challenges and opportunities developers face amid rapid innovation.

1. About Me – As a JD campus recruit, I led AI technology exploration and implementation in a large‑model practice project, integrating cutting‑edge papers, Semantic Kernel, AutoGPT, and other open‑source tools to build the AI system DevBooster , which offers various customized AI capabilities. I also open‑sourced DevBooster, maintained its community, and authored popular technical articles that ranked highly on platforms such as Juejin and CSDN.

2. Anchoring Direction – A Student Adventure – My undergraduate years were marked by “confusion” until a Python programming course let me quickly develop a usable tool, sparking a result‑oriented mindset and a switch to computer science. Through disciplined self‑learning, I mastered Python, C, Java, and explored web crawling, network security, front‑end and back‑end projects, eventually securing an internship at a major tech company.

3. A Dramatic Turn – Growing as a New Professional – After university, I joined JD’s backend team, quickly discovering that the role involves far more than coding: requirement reviews, design, integration, code reviews, and testing dominate the workflow. This experience reshaped my view of backend development as an art of translating complex business needs into reliable, scalable systems, emphasizing architectural thinking.

4. Self‑Iteration – Keys to Becoming an Excellent Backend Engineer – I emphasize lifelong learning, rapid adaptation to new technologies, and proactive skill expansion. I self‑taught C++ to record point‑cloud data with a Kinect, built a dataset, optimized the PointNet model, added multi‑frame fusion, and deployed the solution on a robot using ROS, culminating in a first‑class academic paper.

5. Technical Reflection – Challenges and Opportunities – The rise of AIGC forces backend engineers to continuously learn new paradigms and tools. While some resist AI fearing replacement, the reality is that tools empower those who master them. Embracing AI, we launched the DevBooster test‑generation plugin, organized an internal unit‑test challenge, and helped dozens of core applications generate millions of lines of test code, dramatically improving development efficiency.

Throughout this journey, I have learned that a developer’s impact grows when they expand beyond pure coding—engaging in product, operations, UI design, and knowledge sharing. By sharing technical insights, participating in open‑source, and maintaining a growth mindset, I aim to stay ahead in a fast‑changing industry.