Generative AI Engineer

The candidate will work closely with engineering, product, and data teams to design scalable AI solutions and integrate modern GenAI capabilities into enterprise applications. Key Responsibilities

• Design, develop, and deploy Generative AI and machine learning solutions for enterprise use cases.
• Build applications leveraging LLMs, RAG (Retrieval-Augmented Generation), embeddings, vector databases, and prompt engineering.
• Develop and optimize AI/ML pipelines and production-grade AI services.
• Integrate GenAI capabilities with existing enterprise applications, APIs, and data platforms.
• Evaluate and select appropriate AI models, frameworks, and tools based on business requirements.
• Implement techniques for model evaluation, fine-tuning, grounding, and performance optimization.
• Develop scalable and reliable AI solutions using cloud platforms and modern engineering practices.
• Collaborate with data scientists, software engineers, architects, and business stakeholders.
• Ensure AI solutions meet requirements for security, scalability, performance, and responsible AI.
• Stay current with emerging developments in Generative AI, LLMs, and AI engineering.

We are seeking an experienced Generative AI Engineer with 10+ years of overall software engineering experience to join our team in Charlotte, NC. The ideal candidate will have strong hands-on experience building and deploying AI/ML solutions, with a particular focus on Generative AI, Large Language Models (LLMs), prompt engineering, and AI-powered applications., * 10+ years of software engineering / technology experience.

• Strong hands-on experience with Generative AI and LLM-based applications.
• Proficiency in Python and modern software development practices.
• Experience with frameworks such as LangChain, LlamaIndex, or similar GenAI frameworks.
• Strong understanding of RAG, vector databases, embeddings, prompt engineering, and LLM orchestration.
• Experience working with cloud platforms such as AWS, Azure, or Google Cloud.
• Experience with REST APIs, microservices, and enterprise application integration.
• Knowledge of machine learning concepts and AI model lifecycle management.
• Experience with databases and data processing technologies.
• Strong troubleshooting, analytical, and problem-solving skills.
• Excellent communication and collaboration skills.

Preferred Qualifications

• Experience with Azure OpenAI, OpenAI APIs, AWS Bedrock, Google Vertex AI, or similar platforms.
• Experience with vector databases such as Pinecone, FAISS, Weaviate, or Azure AI Search.
• Knowledge of Docker, Kubernetes, CI/CD, and MLOps/LLMOps.
• Experience implementing AI governance, security, privacy, and responsible AI practices.
• Experience with fine-tuning or adapting foundation models for enterprise use cases.