Generative AI Engineer

Generative AI Engineer (Java/Python)

Location:

Charlotte, NC

We are seeking a skilled Generative AI Engineer with expertise in Java or Python to design, develop, and deploy AI-driven applications leveraging large language models (LLMs), machine learning, and deep learning techniques. The ideal candidate will have strong programming skills, hands-on experience with AI/ML frameworks, and the ability to build scalable and innovative AI-powered solutions.

• Design, develop, and implement Generative AI models for tasks such as text generation, summarization, image generation, code generation, and conversational AI.
• Build APIs and microservices integrating AI models into production systems.
• Fine-tune and optimize pre-trained LLMs (e.g., GPT, LLaMA, Falcon, Mistral, or similar) for business-specific use cases.
• Apply Natural Language Processing (NLP), deep learning, and reinforcement learning techniques to enhance model performance.
• Collaborate with data engineers, ML engineers, and product teams to define use cases and deliver AI-driven solutions.
• Ensure scalability, efficiency, and security of deployed AI models.
• Research and implement the latest trends and advancements in Generative AI.
• Monitor, evaluate, and improve AI systems using appropriate metrics.

• Strong programming skills in Java and/or Python.
• Solid understanding of machine learning, deep learning, and NLP techniques.
• Hands-on experience with frameworks such as Tensor Flow, PyTorch, Hugging Face Transformers, Lang Chain, or Keras.
• Experience working with cloud platforms (AWS, Azure, GCP) for AI/ML deployment.
• Familiarity with API development, microservices, and containerization (Docker, Kubernetes).
• Strong problem-solving skills and the ability to work in an agile, collaborative environment.
• Bachelor’s/Master’s in Computer Science, Data Science, AI/ML, or a related field.

• Experience with vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS).
• Knowledge of prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning LLMs.
• Familiarity with MLOps practices (CI/CD for ML, model monitoring, experiment tracking).
• Prior exposure to Generative AI for enterprise applications (chatbots, copilots, content generation).
• Contributions to open-source AI/ML projects.