Senior AI Engineer - LLM Systems & RAG Optimization
Senior AI Engineer will design and fine‑tune LLM systems to deliver personalized performance insights for athletes and coaches. The role focuses on integrating retrieval‑augmented generation with sports data to create scalable, context‑aware training solutions.
Skills required
About this role
Texas Sports Academy is on the lookout for a Senior AI Engineer specializing in LLM (Large Language Model) Systems and RAG (Retrieval-Augmented Generation) Optimization. As we continue to push the boundaries of sports technology, your role will be pivotal in developing and optimizing AI-driven solutions that enhance our offerings for athletes and coaches. You will be responsible for designing, developing, and fine-tuning LLM systems that can offer personalized insights and performance recommendations based on data-driven analysis. Your expertise in retrieval-augmented generation will enable the integration of comprehensive data sources, empowering our systems to deliver high-quality, context-aware content and responses. You will work collaboratively with data scientists, software engineers, and domain experts to implement scalable AI solutions that drive innovation in our training programs. If you are passionate about harnessing the power of AI to transform the sports industry and have a strong foundation in NLP and machine learning, this is the perfect opportunity for you to make an impact.
Responsibilities
- Design and implement LLM systems tailored to the needs of athletes and coaches.
- Optimize retrieval-augmented generation processes to improve the quality and relevance of AI-generated content.
- Collaborate with cross-functional teams to define AI strategies and ensure alignment with business goals.
- Conduct research on cutting-edge AI methodologies and integrate them into existing systems.
- Monitor and evaluate system performance, making data-driven adjustments as necessary.
- Mentor junior team members and help cultivate a culture of innovation within the department.
- Document system architecture, processes, and best practices for future reference and team knowledge sharing.
Requirements
- Master's degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
- Extensive experience with Large Language Models (LLMs) and retrieval-augmented generation systems.
- Proficient in programming languages such as Python, with a strong understanding of data structures and algorithms.
- Familiarity with AI/machine learning frameworks (e.g., TensorFlow, PyTorch) and NLP libraries.
- Experience with optimizing AI models for efficiency and performance.
- Strong analytical and problem-solving skills with the ability to work effectively in a fast-paced environment.
- Exceptional communication skills to articulate complex concepts to stakeholders and team members.
