Software AI Engineer

Job Title: Software AI Engineer Job Type: Contractual Location: On-site, Washington, District of Columbia, United States Job Summary: We are seeking a talented Software AI 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.