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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal AI ML Software Developer (Onsite) - **Company:** RTX - **Location:** Richardson, TX, United States - **Experience:** Expert - **Salary:** $107,500.0 - $204,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Confluence, JIRA, Automation of Tests, Code Generation, Communications Protocols, Computer Engineering, Continuous Integration, Software Debugging, DevOps, Distributed Systems, Design of User Interfaces, Python (Programming Language), Open Source Technology, Software Architecture, Systems Development Life Cycle, Zero Trust Network Access, Software Engineering, Workflow Management Systems, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Build Management, Containerization, Kubernetes, Information Technology, Deployment Automation, Atlassian Tools, Api Design, Artificial Intelligence Markup Language (AIML), Docker - **Published:** June 17, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=b32cbd3e08d7b19c ## About the Role Do you have experience in Software engineering?, The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: TS/SCI without Polygraph, * Typically requires a degree in Science, Technology, Engineering, or Mathematics (STEM), and a minimum of 8 years of Software Engineering experience. * Experience as a Software Developer, specifically with Python. * Experience with LLMs and popular AI frameworks (e.g., poolside, LangChain). * Experience in prompt engineering, including techniques for complex reasoning, planning, and tool use. * Experience working on a generative AI Agent and/or open-source related project. * The ability to obtain and maintain a U.S. government issued TS/SCI clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance. Qualifications We Prefer * A degree in Computer Science and/or Computer Engineering. * Practical experience applying Zero Trust Security principles. * Experience with platform development and DevOps tools, including containerization (Docker) and orchestration (Kubernetes). * Experience with the Atlassian suite (JIRA, Confluence, etc.) * Familiarity with CI/CD pipelines and deployment automation. * Experience with UI design is preferred * Knowledge of distributed systems, process management, and workflow orchestration. * A conceptual understanding of advanced agentic concepts like A2A communication and multi-agent consensus. * Experience designing and evaluating software architectures for scalable, secure AI-driven systems ## Description This role leads the development of AI-powered software engineering tools by building and orchestrating advanced SDLC agents that improve coding, testing, and CI/CD workflows. It requires strong Python skills and hands-on experience with LLMs, prompt engineering, secure system design, and modern DevOps technologies to deliver scalable, secure AI solutions. What You Will Do * Develop a suite of SDLC agents, each specialized for tasks like requirements analysis, code generation, debugging, and automated testing. * Implement Zero Trust Security principles across the agentic ecosystem. * Design and build a robust, scalable agentic orchestrator to manage and coordinate multiple AI agents. * Develop and integrate Model Context Protocol (MCP) into SDLC agents, allowing agents to use tools. * Craft and refine sophisticated prompts to guide agent behavior and ensure high-quality, reliable outputs from Large Language Models (LLMs). * Implement Agent-to-Agent (A2A) communication protocols, enabling seamless collaboration and information sharing between agents. * Implement API-driven GenAI tools to enhance the CICD Pipeline * Collaborate with product and engineering teams to integrate the agentic system into our existing development workflows. * Write clean, efficient, and well-documented code while following best practices for building AI-driven systems. ## Related Videos - [AI Killed DevOps... 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