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# Software Engineer IV - AI Concepts / Generative AI

- **Company:** American CyberSystems
- **Location:** Raleigh, NC, United States
- **Salary:** $135,200.0 - $145,600.0
- **Contract:** Temporary contract
- **Skills:** Agile Methodology, Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Code Review, Collaborative Software, DevOps, Python (Programming Language), OpenShift, Software Engineering, Google Cloud, Spring Cloud, Large Language Models, Software Security, Generative AI, Git, Git Flow, Infrastructure Automation Frameworks, Machine Learning Operations, Virtual Agents, Software Version Control
- **Published:** July 12, 2026
- **Apply:** https://www.jofdav.com/jobs/58803466-software-engineer-iv-ai-concepts-generative-ai

## About the Role

* Experience in software engineering with solid software development fundamentals.
 * Hands-on experience with Python development.
 * Knowledge of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), and AI agent frameworks such as LangChain or ADK.
 * Understanding of the Software Development Life Cycle (SDLC) and Agile development methodologies.
 * Experience with Git, branching strategies, code reviews, and collaborative software development.
 * Experience with cloud platforms such as Azure, Google Cloud Platform (GCP), or OpenShift.
 * Knowledge of MLOps, LLMOps, DevOps, and Infrastructure as Code.
 * Experience developing secure applications with a cybersecurity-focused mindset.
 * AI certifications from AWS, Google Cloud, or similar platforms are preferred.

## Description

* Design, develop, and implement AI-powered applications using Python and Generative AI technologies.
 * Build intelligent AI agents using frameworks such as LangChain, Agent Development Kit (ADK), or similar frameworks.
 * Develop proof of concepts (POCs) and prototypes to solve business challenges using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
 * Collaborate with product managers, architects, and engineering teams to deliver scalable AI solutions.
 * Follow Software Development Life Cycle (SDLC) best practices, including version control, code reviews, testing, and deployment.
 * Participate in weekly demonstrations showcasing AI solutions and innovative business use cases.
 * Develop secure, scalable, and cloud-native applications using Azure, GCP, OpenShift, or similar cloud platforms.
 * Apply MLOps and LLMOps best practices to deploy and maintain AI applications.
 * Ensure solutions meet enterprise architecture, security, compliance, and performance standards.
 * Continuously evaluate emerging AI technologies and recommend innovative solutions that drive business value.


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