AI/LLM Engineer

Job Title: AI/LLM Engineer – Generative AI Solutions
Location: Charlotte, NC

Job Overview:

We are looking for a highly skilled AI/LLM Engineer with deep experience in building and deploying Generative AI applications using modern frameworks and cloud infrastructure. This role focuses on designing scalable, production-ready AI systems powered by LLMs, LangChain, LangGraph, and other state-of-the-art tools. The ideal candidate thrives in dynamic environments, collaborates across teams, and is passionate about applying cutting-edge technologies to real-world business problems.

Key Responsibilities:

• Build and deploy LLM-powered applications using LangChain and LangGraph, including integration with external tools and development of stateful workflows with GraphDB.

• Develop and optimize models using Python, TensorFlow, PyTorch, and HuggingFace.

• Scale and deploy AI models into production using MLOps tools like MLflow and Kubeflow.

• Leverage Google Cloud Platform (GCP) services to manage AI pipelines and infrastructure.

• Work with Scala for processing large-scale data sets and support distributed AI applications.

• Implement back-end APIs and services using Java, JavaScript (Node.js).

• Utilize SQL and NoSQL databases (e.g., MongoDB, Cassandra) to manage structured, semi-structured, and unstructured data.

• Collaborate with cross-functional teams and stakeholders to understand business requirements and deliver AI-driven solutions.

• Build quick prototypes to demonstrate feasibility and business value of AI use cases.

• Ensure all models are explainable, well-documented, and compliant with internal and external regulatory standards.

• Maintain a modular, reusable codebase for faster development cycles.

• Follow Agile development practices and actively participate in sprint planning, retrospectives, and reviews.

• Prepare detailed technical documentation for models, processes, and deployments that meet audit and compliance standards.

Required Qualifications:

• Proven expertise in Python, and deep experience with TensorFlow, PyTorch, and HuggingFace.

• Hands-on experience with LangChain and LangGraph for building GenAI workflows.

• Strong proficiency in ML Ops practices and tools such as MLflow and Kubeflow.

• Advanced knowledge of GCP, with experience deploying production systems.

• Experience in Scala for data-intensive processing.

• Back-end development skills in Java and Node.js.

• Deep understanding of SQL and NoSQL data systems.

• Strong problem-solving, analytical, and critical thinking abilities.

• Ability to manage multiple projects, prioritize tasks, and work both independently and within a team.