AI Engineer - Fulltime

Job Title: AI Engineer

Skill Digital: Artificial Intelligence (AI)

Minimum Experience: 8 - 14 Years

Location: Jersey City, NJ

Must have:

• Hands-on Claude Code experience: navigate unfamiliar codebases, perform multi-file refactors, run tests, and manage git workflows through agentic execution.
• Proven reverse engineering skills: produce reverse-engineered requirement documents/PRDs with code-to-function traceability and convert outputs into user stories (e.g., Jira).
• Strong Java + Spring Boot microservices engineering: REST APIs, scalable service design, persistence (RDBMS/NoSQL), and enterprise delivery.
• CI/CD + Kubernetes + Git-based delivery with automated testing and quality gates.
• Modernization mindset combining reverse engineering forward engineering (rewrite/replace/refactor patterns).
• Working knowledge of policy administration modernization context: product rules (UW/form/rating), core policy engine concepts, and coexistence/integration considerations.

Responsibilities:

• Use Claude Code to analyze and navigate large, unfamiliar codebases, performing agentic multifile refactoring, test execution, and Gitbased source control operations.
• Lead AIdriven reverse engineering to extract business logic and functional behavior from legacy systems, producing reverseengineered PRDs and functional requirement documents with clear codetofunction traceability, and translating them into user stories (e.g., Jira).
• Design and develop Java and Spring Boot based microservices, implementing scalable REST APIs, business services, and data persistence using RDBMS and/or NoSQL technologies.
• Build and integrate services into CI/CD pipelines, ensuring Kubernetesbased deployment, automated testing, and enforcement of quality gates.
• Apply a modernization engineering approach, combining reverse engineering and forward engineering techniques to support rewrite, refactor, and replace patterns aligned to the target architecture.
• Ensure functional alignment with policy administration modernization objectives, including product rules (underwriting, forms, rating), core policy engine behavior, and coexistence/integration with legacy systems.