Hi
We have an urgent role of Java/AI role.
URGENT HIRE!
Java/AI role
Remote - EST schedule
6 mos to start - contract to hire
Candidates will be required to take an online technical test from client that won't allow the use of AI
Seeking a Software Engineer who thrives on solving complex technical problems in large-scale enterprise applications. This role is focused on investigating customer-reported issues, performing root-cause analysis, navigating complex Java codebases, and developing production-ready code fixes. The ideal candidate enjoys debugging challenging problems, working directly with customers, and delivering high-quality solutions that improve product stability and performance.
Required:
• 2-5 yrs of software engineering.
• Excellent communication (oral & written), analytical and troubleshooting skills.
• OS experience in one or more areas of Linux, UNIX, and/or Windows.
• Frameworks: Java, J2EE, Servlets, MDB, HTML, JNDI, Jax-RS, JMS, Junit, XML, JSON
• Protocols: AS2/4, HTTP(S), FTP(S), SFTP, Rest/APIs, RNIF, EBICS
• Cloud experience in one or more areas of AWS, Azure, Google, IBM, RedHat.
• CI/CD: Maven, Docker, IBM Cloud, Kubernetes, Jenkins, GitHub
• Database experience in one or more areas of Oracle and/or DB2 and/or MS SQL and/or MySQL
• Ability to read and code through an Object-Oriented Language, preferred Java.
• Experience with JDBC, JDK, JVM stack traces.
• Strong understanding & experience of executing Static & Dynamic scans, fixing vulnerabilities.
• Aptitude to prioritize and handle multiple issues simultaneously.
• Strong attention to detail and accuracy.
• Ability to work independently in a fast-paced environment.
• Ability to function and contribute in a team environment.
Required AI Skills/Knowledge:
• Hands-on experience using AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, or similar tools to understand complex code, accelerate debugging, generate unit tests, improve documentation, and support code review activities.
• Ability to apply AI tools in customer escalation scenarios, including log analysis, defect diagnosis, root-cause investigation, impact assessment, and identification of safe production code fixes.
• Working knowledge of responsible AI practices, including validation of AI-generated output, protection of confidential customer/product data, secure prompt usage, and awareness of bias, hallucination, and explainability considerations.