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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Developer - **Company:** THE JUDGE GROUP, INC. - **Location:** Southlake, TX, United States - **Experience:** Expert - **Salary:** $176,800.0 - $187,200.0 - **Contract:** Temporary to permanent - **Skills:** Java (Programming Language), Agile Methodology, Artificial Intelligence, Amazon Web Services, Automation of Tests, Cloud Computing, Cloud Engineering, Cloud Foundry, COBOL (Programming Language), Databases, IBM DB2, Spring Framework, PostgreSQL, Mainframes, Enterprise Messaging Systems, Microsoft Visio, MongoDB, Systems Development Life Cycle, RabbitMQ, Software Deployment, Software Engineering, SQL Databases, Web Services, Aerospike, Google Cloud, Test-Driven Development (TDD), GitHub Copilot, Large Language Models, Prompt Engineering, Generative AI, Information Technology, Atlassian Tools, Apache Kafka, Virtual Agents, Code Restructuring, GPT, Api Management, Microservices - **Published:** June 1, 2026 - **Apply:** https://www.dice.com/job-detail/f9d3221e-7196-4c5a-89f0-0801a908dcb9 ## About the Role Bachelor's degree in Computer Science, Software Engineering, a related technical field, or equivalent practical experience. 7 years of professional software engineering experience actively developing large-scale software using Java, Spring framework, cloud development, and Web Services supporting high-volume transactions in highly available environments. 6 years of experience working with containers and microservices in a cloud environment. 6 years of experience with cloud deployment in a continuous integration and continuous delivery (CI/CD) model. 2 years of hands-on experience with AI/ML implementation, production deployment, and working with Large Language Models (e.g., GPT-5, Claude, Gemini, PaLM). 2 years of experience working with cloud platforms such as AWS, Google Cloud Platform, or Pivotal Cloud Foundry (PCF). 2 years of experience working with databases including MongoDB, Aerospike, and/or PostgreSQL. 2 years of experience in IT transformations and system modernization initiatives (e.g., migrating legacy Mainframe Cobol/DB2 applications to distributed Java/SQL/MongoDB platforms). Hands-on experience using Generative AI coding assistants (e.g., GitHub Copilot, Claude Code) within IDE/CLI-style workflows across the Software Development Life Cycle (SDLC). Practical experience with agentic workflows, prompt engineering, and spec-driven development. Domain expertise and foundational understanding of broker-dealer capabilities and operations. Preferred qualifications: Master's degree in Information Technology, Computer Science, or a related technical field. Professional experience within the Financial Services industry. Strong knowledge of messaging technologies (e.g., RabbitMQ, Kafka, or equivalent). Experience with Test Driven Development (TDD), QA Automation, and a strong quality-assurance mindset. Proficiency in developing architectural and design documentation, functional and technical specifications, and diagrams (e.g., Visio). Experience in an Agile working environment utilizing the Atlassian tool stack (JIRA and Confluence). Proven ability to research, learn, and comprehensively document complex tech stacks, including production/test environments and architecture designs. Excellent communication skills with a proven ability to lead and mentor other engineers in a collaborative setting. ## Description Lead AI-focused engineering workflows across the entire System Development Life Cycle (SDLC). Leverage AI assistance for daily development tasks-including code suggestions, test generation, refactoring, review support, scripting/automation, and troubleshooting-while maintaining clear ownership over code correctness and quality. Apply Generative AI strategies to reduce context switching and accelerate delivery across various engineering workflows. Translate low-level design artifacts (such as class structures, API contracts, and data models) into structured specifications to guide AI-assisted implementation. Establish and advocate for team-level best practices regarding effective AI-assisted development, custom instructions, and prompt engineering. Maintain a strong execution focus and a bias for action to effectively collaborate with fellow developers, software architects, and cross-functional teams. ## Related Videos - [Data Fabric in Action - How to enhance a Stock Trading App with ML and Data Virtualization](https://www.wearedevelopers.com/videos/253-data-fabric-in-action-how-to-enhance-a-stock-trading-app-with-ml-and-data-virtualization) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [40 Minutes to Build a Serverless COVID-19 REST and GraphQL APIs](https://www.wearedevelopers.com/videos/208-40-minutes-to-build-a-serverless-covid-19-rest-and-graphql-apis) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Agentic employees in world's most downloaded FinTech app](https://www.wearedevelopers.com/videos/100123-agentic-employees-in-world-s-most-downloaded-fintech-app) - [NoSQL Data Modeling for Front-end Developers](https://www.wearedevelopers.com/videos/297-nosql-data-modeling-for-front-end-developers) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Got AI ideas but no money? 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