AI Native Java Developer Hiring Hackathon

Zycus is a global leader in Source-to-Pay (S2P) procurement software, helping large enterprises drive efficiency, compliance, and measurable value across their procurement and finance operations. Trusted by leading Fortune 1000 organizations worldwide, Zycus enables procurement teams to move from cost control to strategic value creation.

At the core of Zycus’ platform is Merlin AI, an advanced AI-powered engine that brings intelligence, automation, and predictive insights across the entire procurement lifecycle—from sourcing and contract management to procurement, invoicing, and supplier management. Merlin AI empowers Chief Procurement Officers and finance leaders to make faster, smarter decisions with real-time visibility and actionable insights.

Zycus is consistently recognized by top industry analysts such as Gartner, Forrester, and IDC for its innovation, depth of functionality, and strong customer outcomes. Known for its enterprise-grade solutions, global delivery model, and customer-first mindset, Zycus partners closely with organizations to modernize procurement and unlock long-term business value.

With a strong global presence across North America, EMEA, and APAC, Zycus continues to invest aggressively in product innovation, AI-led capabilities, and brand leadership—shaping the future of intelligent procurement.

We Are An Equal Opportunity Employer:
Zycus is committed to providing equal opportunities in employment and creating an inclusive work environment. We do not discriminate against applicants on the basis of race, color, religion, gender, sexual orientation, national origin, age, disability, or any other legally protected characteristic. All hiring decisions will be based solely on qualifications, skills, and experience relevant to the job requirements.

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 (Date: Sat, 30th May 9:00 AM, Mumbai)

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.