LLM Engineer

Job Title:
LLM Engineer

Job Type:
Full-time, Contractual

Location:
On-site, Washington, District of Columbia, United States

Job Summary:

We are seeking a talented LLM Engineer to join our customer's team in Washington, DC. This is a unique opportunity to work on cutting-edge AI/ML projects, leveraging the latest advancements in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and full-stack development. If you are passionate about building innovative solutions and thrive in a collaborative on-site environment, we want to hear from you.

Key Responsibilities:

• Design, develop, and maintain applications utilizing LLMs and RAG methodologies.
• Implement and scale AI/ML models using frameworks like TensorFlow and PyTorch.
• Build and maintain robust front-end interfaces with React and scalable back-end systems with Node.js.
• Collaborate closely with cross-functional teams to translate business requirements into technical solutions.
• Deploy and manage applications on AWS, ensuring reliability, security, and scalability.
• Continuously research and integrate the latest technologies in AI/ML and cloud computing.
• Communicate complex technical concepts clearly, both in writing and verbally, to diverse stakeholders.

Required Skills and Qualifications:

• Proven experience with LLMs using APIs, fine-tuning, RAG, or pre/post training development workflows.
• Strong development skills in JavaScript/TypeScript with hands-on experience in React and Node.js.
• Solid understanding of AI/ML concepts and practical experience with frameworks such as TensorFlow or PyTorch.
• Expertise in deploying and managing applications on AWS or similar cloud platforms.
• Proficiency in common full stack frameworks and best practices.
• Exceptional written and verbal communication skills, with a focus on clarity and collaboration.
• Demonstrated ability to work effectively on-site in a collaborative, fast-paced team environment.

Preferred Qualifications:

• Experience with additional AI/ML frameworks and cloud-native technologies.
• Background in Retrieval-Augmented Generation (RAG) architectures and prompt engineering.
• Track record of delivering production-grade AI/ML solutions in a full-stack environment.