Gen AI Engineer

Gen AI Engineer

Hybrid in Charlotte, NC (2 days per week in office)

As a GAI Expert/Software Engineer, you will be responsible for building an application that generates code, pipelines, and creates web applications automatically via prompts. You will also play a key role in enhancing our contact center operations using generative AI frameworks. This role requires a deep understanding of AI, machine learning, and software engineering principles, as well as a strong foundation in writing maintainable, testable, and modular code.

Key Responsibilities:

• Design, develop, and maintain applications that generate code, pipelines, and web applications automatically via prompts using generative and agentic AI.
• Enhance contact center operations by integrating generative AI solutions that improve customer experience and operational efficiency.
• Apply software design principles and common patterns to write clean, maintainable, and scalable code.
• Leverage unit testing frameworks to ensure code quality and reliability.
• Experiment with and implement cutting-edge LLM agentic technologies to enhance application capabilities.
• Collaborate with cross-functional teams and business stakeholders to accelerate adoption of AI-powered tools.
• Implement GAI solutions in alignment with Duke Energy AI Policies.
• Conduct R&D to explore new AI techniques and future technologies such as blockchain and quantum computing.
• Optimize and fine-tune AI models for performance, scalability, and accuracy.
• Provide technical guidance and mentorship to junior team members.

Preferred Qualifications:

• Proven experience in software engineering with a focus on AI and machine learning.
• Experience with agentic technologies and their applications.
• Familiarity with generative AI frameworks and LLMs.
• Knowledge of natural language processing (NLP) and computer vision.
• Experience with DevOps practices and tools for CI/CD.
• Strong programming skills in Python, React, Angular.
• Experience with AWS cloud platform and services.
• Familiarity with modularized, testable code and unit testing frameworks.
• Appetite for continuous learning and staying current with emerging AI technologies.
• Excellent problem-solving, communication, and collaboration skills.