AI Agentic Engineer

Role Description The AI Agentic Engineer is a full-time hybrid role based in Irving, TX, with flexibility for part-time work from home. This role involves designing, building, and optimizing AI agents and intelligent systems that can autonomously analyze data, interact with users, and integrate with existing software platforms. Day-to-day responsibilities include developing and testing machine learning models, implementing pattern recognition and neural network solutions, and integrating NLP capabilities to improve agent performance and usability. The AI Agentic Engineer will collaborate closely with software developers, product managers, and other stakeholders to translate business requirements into technical designs, ensure reliable deployment in production environments, and monitor system performance. The role also includes reviewing new tools and frameworks, documenting technical designs, and contributing to best practices for secure, maintainable AI systems.

Qualifications

• Strong foundation in Computer Science, including data structures, algorithms, and software architecture.
• Hands-on experience in Software Development, with proficiency in at least one modern programming language (e.g., Python, Java, or C++).
• Practical skills in Pattern Recognition and Neural Networks, including building, training, and evaluating machine learning models.
• Experience with Natural Language Processing (NLP), such as intent detection, text classification, conversational AI, or LLM-based solutions.
• Familiarity with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, LangChain, or similar agentic frameworks).
• Ability to design, test, and deploy production-ready AI services and APIs, including experience with version control and CI/CD.
• Strong analytical and problem-solving skills, with the ability to work independently and in cross-functional teams in a hybrid environment.
• Bachelor’s degree in Computer Science, Engineering, or a related technical field; equivalent practical experience is also considered.
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization (Docker, Kubernetes) is beneficial.
• Clear written and verbal communication skills and interest in staying current with developments in AI and agentic systems.