Location: Charlotte
Employment Type: Full-Time
Experience Level: 5+ Years in Full Stack Development; 2+ Years in AI/ML Integration Preferred

Position Overview

We are seeking a highly skilled and forward-thinking Full Stack Engineer – Generative AI Solutions to design, develop, and deploy end-to-end applications enhanced with GenAI capabilities. You will be at the forefront of integrating cutting-edge generative models (e.g., LLMs, Transformers) into production-grade applications. This role demands strong engineering fundamentals, full-stack proficiency, and a passion for leveraging AI to build intelligent systems.

Key Responsibilities:

• Develop and deploy GenAI-powered features across front-end, back-end, and database layers.
• Integrate Large Language Models (LLMs) and other generative models into new and existing software systems.
• Design and manage CI/CD pipelines optimized for GenAI model deployment and updates.
• Build and maintain efficient, reliable data pipelines for GenAI model training and inference.
• Write clean, modular, testable, and well-documented code.
• Troubleshoot and debug full-stack and AI model integration issues in production environments.
• Collaborate cross-functionally with product, data science, and design teams.
• Stay current on GenAI trends, frameworks (e.g., Agentic AI), and full-stack technologies.
• Work with AI/ML model APIs and platforms such as OpenAI, Hugging Face, or Google Vertex AI.

Required Qualifications:

• Proficiency in multiple programming languages such as Python, JavaScript, and Java.
• Solid hands-on experience with modern front-end frameworks: React, Angular, or Vue.js.
• Strong back-end development expertise using Node.js, Flask/Django, or Spring.
• Experience with SQL and NoSQL databases.
• Familiarity with cloud platforms, especially AWS (e.g., Lambda, S3, SageMaker).
• Strong understanding of CI/CD practices, DevOps, and SDLC principles.
• Experience with Docker and Kubernetes for containerization and orchestration.
• Hands-on integration of AI/ML models into production applications.
• Deep understanding of GenAI concepts, including LLMs, transformers, embeddings, and prompt engineering.
• Exposure to frameworks such as LangChain, AutoGen, or Agentic AI.

Application Process: Please submit your resume, cover letter, and examples of GenAI projects or architectures you’ve led. Include specific details about your experience integrating AI models into enterprise systems and your approach to leading technical teams.