AI-Native Java Developer Mumbai Hackathon

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 JavaUse AI coding assistants effectivelyReview, debug, and improve AI-generated codeThink architecturally, not just syntacticallyMove fast while maintaining engineering qualityWork like modern AI-first software engineersThis 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 discussionAI coding workflow discussionLive code review exerciseGitHub profile reviewCommunication and problem-solving evaluationWe are specifically evaluating:

How you thinkHow you review codeHow you use AI tools effectivelyStage 2 - AI Native Java 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 laptopTheir preferred development setupActive 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 AIPrompt engineering for developmentSpeed of implementationArchitecture decisionsDebugging capabilityAI-generated code validationEngineering judgmentGit disciplineProduct thinkingSubmission Process

At the end of the hackathon:

Candidates will upload their code to GitHubShare a public repository linkSubmit implementation notes and approachOur engineering and AI review systems will evaluate:

Code qualityAI usage patternsSystem designMaintainabilityProduction readinessFinal Technical Discussion

Top candidates will then participate in a final engineering interaction focused on:

Architecture choicesAI-assisted development approachTradeoffs and scalabilityDebugging walkthroughOwnership mindsetWhy This Hiring Model Is Different

Traditional hiring tests memory. We want to test modern engineering capability.

The best engineers today:

Use AI effectivelyMove rapidlyValidate intelligentlyBuild efficientlyThink criticallyThis hiring challenge is designed to identify exactly those engineers.