Zycus
Website:
zycus.com
Job details:
Become An AI Native Engineer- Build real systems with AI. Compete with Top Developers. Get Hired
We are launching a high-intensity hiring challenge to identify the next generation of AI Native Java Developers — engineers who don’t just write code, but know how to collaborate with AI to build production-grade systems faster and smarter.
If you use tools like Cursor, GitHub Copilot, Claude, ChatGPT, Windsurf, or other AI coding assistants as part of your daily workflow, this hiring drive is designed for you.
Build with AI. Code with Speed. Get Hired.
“A modern engineering hiring experience designed for AI-native developers.”
What we are looking for?
We are hiring developers who can:
- Build scalable backend systems using Java
- Use AI coding assistants effectively
- Review, debug, and improve AI-generated code
- Think architecturally, not just syntactically
- Move fast while maintaining engineering quality
- Work like modern AI-first software engineers
This is not a traditional coding test. This is a real-world AI engineering challenge.
Hiring Process:
Stage 1 - HR + Technical Screening Interview
Shortlisted candidates will attend an initial screening discussion.
This includes:
- Candidate background discussion
- AI coding workflow discussion
- Live code review exercise
- GitHub profile review
- Communication and problem-solving evaluation
We are specifically evaluating:
- How you think
- How you review code
- How you use AI tools effectively
Stage 2 - AI Native Hackathon
The Challenge
Top 20 candidates will be invited for an in-person hackathon where they will build a working software system within 5 hours. (Details will be emailed to the shorlisted candidates)
Important:
Candidates must bring:
- Their own laptop
- Their preferred development setup
- Active AI coding assistant tools (Cursor, Copilot, etc.)
We intentionally want candidates working in their own environment because modern engineering productivity depends on developer tooling mastery.
What We Will Evaluate
This is NOT just about writing code manually.
We want to observe:
- How you collaborate with AI
- Prompt engineering for development
- Speed of implementation
- Architecture decisions
- Debugging capability
- AI-generated code validation
- Engineering judgment
- Git discipline
- Product thinking
Submission Process
At the end of the hackathon:
- Candidates will upload their code to GitHub
- Share a public repository link
- Submit implementation notes and approach
Our engineering and AI review systems will evaluate:
- Code quality
- AI usage patterns
- System design
- Maintainability
- Production readiness
Final Technical Discussion
Top candidates will then participate in a final engineering interaction focused on:
- Architecture choices
- AI-assisted development approach
- Tradeoffs and scalability
- Debugging walkthrough
- Ownership mindset
Why This Hiring Model Is Different
Traditional hiring tests memory. We want to test modern engineering capability.
The best engineers today:
- Use AI effectively
- Move rapidly
- Validate intelligently
- Build efficiently
- Think critically
This hiring challenge is designed to identify exactly those engineers.
Click on Apply to know more.