Why Campus Recruitment Often Leads to Small‑Mid‑Size Companies: A Student’s Interview Journey

When scrolling through job platforms, most interview experiences seem to come from internet giants like ByteDance, Alibaba, or Tencent, creating the illusion that everyone holds a high‑salary offer from a big‑tech firm. In reality, the majority of job seekers end up at the myriad small‑ and medium‑sized companies that sustain daily life.

First Interview – Transportation Group (Big‑Data, State‑Owned)

The interview process was very academic: a written test followed by a resume review. The written test (≈1 hour) covered basic fundamentals such as writing regular expressions, designing tables and complex SQL queries, and explaining callback usage in a framework. The interview (≈40 minutes) focused almost entirely on Java basics, with the project serving only as a garnish.

Java fundamentals: annotations, reflection, HashMap internals and resizing, ConcurrentHashMap principles, differences among String, StringBuilder, and StringBuffer.

Frameworks & middleware: JWT authentication, Redis single‑thread model and distributed locks, cache pitfalls (avalanche, penetration, breakdown), message‑queue roles.

Databases: index invalidation scenarios, clustered vs. non‑clustered indexes, index push‑down.

Concurrency: thread‑pool core parameters and rejection policies.

The environment felt a bit stale, but the interviewers were professional and the process was orderly.

Second Interview – AI & Blockchain Startup

This fast‑paced company skipped the written test and dove straight into project deep‑dive questions. The interview (≈30 minutes) was conducted by two interviewers and emphasized project experience over rote knowledge.

Business understanding: "Describe your project's workflow and the implementation of the payment module."

Technology selection: "Why choose Spring AI instead of LangChain4j? Compare the two."

Core concepts: Explanation of Retrieval‑Augmented Generation (RAG).

Engineering practice: Document chunking criteria and handling semantic gaps.

Prompt engineering: Design and optimization of prompts.

Additional probing questions covered:

Why does HashMap convert a long linked list into a red‑black tree?

Differences between MySQL B+‑tree and B‑tree, ACID guarantees, and other SQL optimization techniques.

The essence of IOC and AOP, and concrete AOP usage in a project.

Redis RDB vs. AOF, and how RocketMQ ensures message reliability from producer to consumer.

Later Interviews – ToB/ToG Business Company & Financial AI Firm

The ToB/ToG interview was brief, resembling an HR screening with a casual self‑introduction and vague discussion of studies and projects.

The financial AI company provided the most rewarding experience (≈45 minutes). Questions interleaved project discussion with core Java topics, and the interviewers pursued each answer with two to three follow‑up layers, offering constructive hints and corrections.

Reflections and Growth

Mindset evolution: The candidate became noticeably calmer, able to think through unknown questions without panicking.

Professional dialogue: The interview felt like a high‑quality technical exchange rather than a cold assessment.

Feedback: The interviewer praised the candidate’s solid technical foundation for a junior, noting the need to deepen project insight and boost confidence in expression.

Key takeaways:

Core Java knowledge is the "entry ticket," but project depth forms the "moat" that determines interview success.

Interviews act as the best "technical health check," quickly exposing gaps in one’s knowledge base.

Confidence stems from both preparation and practice; speaking more, even imperfectly, outweighs silent anxiety.

Ultimately, the road of campus recruitment is long and winding, but perseverance leads to progress.