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AI Assisted Fullstack Java Engineer

Not Disclosed

Job Description & Details

This is a hands-on, senior-level individual contributor role focused on spearheading AI-assisted software delivery for an enterprise environment. They need someone who already knows how to squeeze velocity out of tools like Claude and Cursor without letting code quality slip.

What You'll Actually Be Doing

You'll be jumping straight into the thick of things, owning features from design to production hardening while mentoring the team on how to actually use AI responsibly. Because the client has limited resources and strict licensing, you won't get a ramp-up period to learn AI tools—you're expected to come in as the SME, driving Java backend and React frontend development while evaluating whether AI-generated code will actually survive in a real production pipeline.

The Core Tech Stack

Backend Java is an absolute non-negotiable requirement, paired closely with React on the frontend and deep, practical experience using Anthropic Claude or Cursor for rapid refactoring and code generation. You also need rock-solid engineering fundamentals, meaning you can't just copy-paste from an LLM; you need strong design patterns and the architectural maturity to vet, secure, and harden AI outputs before they touch a deployment pipeline.

Interview Expectations

Expect them to hand you a messy snippet of AI-generated Java code and ask you to spot the subtle security vulnerabilities or performance bottlenecks hidden inside it. The hiring manager is secretly testing your engineering judgment to ensure you treat AI as an accelerator rather than a replacement for your own brain. They will also want to hear about your exact prompt engineering workflows and how you handle state management or error handling in hybrid architectures.

Application Advice

Skip the generic summaries and weave the exact keywords from this listing—specifically Java, React, Anthropic Claude, Cursor, and production hardening—directly into your resume experience bullets. Show concrete examples of how you've used AI coding assistants to cut down development cycles on enterprise Java apps while maintaining rigorous test coverage and security standards to easily clear their ATS.