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# Software Engineer

- **Company:** CoreLogic, Inc.
- **Location:** Irving, TX, United States
- **Experience:** Starter
- **Salary:** $93,200.0 - $115,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Software Quality, Databases, Continuous Integration, Software Debugging, Programming Tools, Revision Control Systems, Python (Programming Language), Software Architecture, Systems Development Life Cycle, Microsoft Copilot, Software Engineering, Software Systems, TypeScript, Software Organization, Enterprise Software Applications, Spring Cloud, LangChain, Large Language Models, Prompt Engineering, Model Validation, Generative AI, Agentic-AI, Information Technology, CrewAI, AutoGen, Semantic Kernel, Devsecops, Programming Languages
- **Published:** November 6, 2026
- **Apply:** https://www.disabledperson.com/jobs/76388821-software-engineer

## About the Role

* Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience.
 * 3+ years of professional software engineering experience developing and supporting enterprise applications.
 * Proficiency in one or more modern programming languages such as Java, C#, Python, JavaScript, or TypeScript.
 * Experience with cloud platforms, APIs, databases, and modern software development practices.1-2 years of hands-on experience working with AI-enabled applications, generative AI technologies, AI assistants, agentic workflows, or large language model (LLM) integrations.
 * Understanding of AI SDLC concepts, including AI-assisted development, prompt engineering, model evaluation, testing, governance, security, and responsible AI practices.
 * Experience using modern development tools, source control systems, CI/CD pipelines, and Agile delivery methodologies.
 * Strong analytical, troubleshooting, communication, and collaboration skills., * Experience building AI agents or orchestrating multi-step workflows using frameworks such as LangChain, Semantic Kernel, AutoGen, CrewAI, or similar technologies.
 * Familiarity with AI-assisted engineering platforms and tools used throughout the AI SDLC (ex: BMAD, Speckit, VS Code, Copilot).
 * Experience developing cloud-native applications on Azure, AWS, or Google Cloud.Knowledge of software architecture, observability, automated testing, and DevSecOps practices.
 * Passion for leveraging AI to improve engineering productivity, software quality, and business outcomes.

## Description

* Design, develop, test, deploy, and maintain scalable software applications following established engineering standards, coding best practices, and architectural guidelines under general supervision.
 * Collaborate with product managers, designers, architects, and fellow engineers to translate business requirements into high-quality software solutions.
 * Participate in all phases of the software development lifecycle (SDLC), including requirements analysis, design, implementation, testing, deployment, monitoring, and maintenance.
 * Write clean, maintainable, secure, and efficient code that meets functional and non-functional requirements.
 * Conduct peer code reviews, contribute to engineering best practices, and provide constructive feedback to help improve overall code quality.
 * Troubleshoot, debug, and resolve application issues to ensure reliability, performance, and scalability.
 * Contribute to the development and integration of AI-enabled features, services, or workflows, including working with large language models (LLMs), AI agents, and AI-assisted development tools.Assist in the design, testing, and evaluation of agentic workflows and AI-powered solutions while applying responsible AI, security, and governance practices.
 * Leverage AI development tools and automation capabilities to improve developer productivity, software quality, and delivery speed.
 * Participate in continuous improvement efforts related to AI Software Development Lifecycle (AI SDLC) practices, including prompt engineering, model evaluation, testing, observability, and deployment processes.