Generative AI Engineer

Job Title: Senior Azure GenAI Engineer (with MLOps & LLM Expertise)

Location: Nashville, TN (Day 1 Onsite)

Experience: 8-10 Years

Job Overview:

We are seeking a Senior Azure GenAI Engineer to join our team in Nashville, TN. The ideal candidate will have in-depth experience with Azure, Generative AI (GenAI), Large Language Models (LLM), and MLOps. This role is designed for professionals who have a strong background in machine learning, AI model deployment, and integrating MLOps processes for seamless, scalable AI operations. The individual will also work closely with cutting-edge technologies such as Retrieval-Augmented Generation (RAG) to optimize and enhance AI systems.

Key Responsibilities:
• Lead and manage Azure cloud environments for deploying and scaling AI models, including GenAI and LLM-based solutions.
• Design, develop, and implement end-to-end machine learning pipelines, from model training to deployment in production environments.
• Leverage MLOps best practices for continuous integration/continuous delivery (CI/CD) of machine learning models.
• Collaborate with cross-functional teams to optimize AI workflows, ensuring models and solutions are scalable, efficient, and cost-effective.
• Utilize Retrieval-Augmented Generation (RAG) techniques to improve the quality of generative AI responses and data retrieval.
• Provide mentorship and guidance to junior engineers, helping to drive innovation and adoption of best practices across teams.
• Stay up-to-date with the latest trends in AI, machine learning, and Azure technologies, and apply them to current projects.

Required Skills and Experience:
• 8-10 years of professional experience in AI, machine learning, and cloud technologies.
• Strong hands-on experience with Azure services (e.g., Azure Machine Learning, Azure Databricks, etc.) for deploying AI solutions.
• Expertise in Generative AI (GenAI) and Large Language Models (LLM).
• Strong experience in MLOps, including tools such as Azure DevOps, MLflow, or similar platforms.
• Experience in developing, deploying, and managing AI models with a focus on scaling and automation.
• Understanding of Retrieval-Augmented Generation (RAG) and its application in AI solutions.
• Proficient in Python, TensorFlow, PyTorch, or similar machine learning frameworks.
• Excellent communication and collaboration skills, with the ability to work effectively in a cross-functional team.

Preferred Qualifications:
• Experience with additional cloud platforms (e.g., AWS, GCP).
• Familiarity with containerization technologies like Docker and Kubernetes for model deployment.
• Advanced degree in Computer Science, AI, Data Science, or related fields.