AI - Data Engineer

Who We Are

Creative Artists Agency (CAA) is the leading entertainment and sports agency, with global expertise in filmed and live entertainment, digital media, publishing, sponsorship sales and endorsements, media finance, consumer investing, fashion, trademark licensing, and philanthropy. Distinguished by its culture of collaboration and exceptional client service, CAA’s diverse workforce identifies, innovates, and amplifies opportunities for the people and organizations that shape culture and inspire the world.

The trailblazer of the agency business, CAA was the first to build a sports business, create an investment bank, launch a venture fund, found technology start‑up companies, establish a philanthropic arm, build a business in China, and form a brand marketing services division, among other innovations. Named Most Valuable Sports Agency by Forbes for eight consecutive years, CAA represents more than 2,000 of the world’s top athletes in football, baseball, basketball, hockey, soccer, in addition to coaches, on‑air broadcasters, and sports personalities and works in the areas of broadcast rights, corporate marketing initiatives, social impact, and sports properties for sales and sponsorship opportunities.

Founded in 1975, CAA is headquartered in Los Angeles, and has offices in New York, Nashville, Memphis, Chicago, Miami, London, Munich, Geneva, Stockholm, Shanghai, and Beijing, among other locations globally.

The AI Engineer is a member of a highly motivated CAA Tech team responsible for accelerating the creation of opportunity through the strategic use of data. In this role, you will design and build intelligent systems that transform complex information into structured knowledge and actionable insights using modern AI, machine learning, and generative approaches to solve complex business problems. You will operate across the full lifecycle, from experimentation and evaluation to deployment and optimization, developing solutions that ingest, interpret, and reason over large volumes of data.

The ideal candidate combines strong software engineering fundamentals with hands on experience building applied AI systems that operate reliably in production environments and deliver measurable business impact.

• Design and implement end to end AI workflows for complex data interpretation, knowledge extraction, and reasoning
• Build systems that convert unstructured content into structured representations
• Develop and optimize retrieval approaches that combine semantic and lexical search techniques
• Prototype, evaluate approaches, test feasibility, and product ionize generative AI solutions for real world use cases
• Partner with engineering teams to develop technology infrastructure
• Optimize systems for latency, cost, and throughput

• Design and implement evaluation approaches to assess performance, relevance, and effectiveness of AI solutions
• Apply techniques to improve consistency, accuracy, and trustworthiness of outputs
• Implement methods for scoring, explainability, and ongoing quality assurance

• Identify data sources that can be useful to answer business questions
• Perform experiments on ingested data to evaluate quality and integrity
• Build data pipelines for ongoing data extraction

• Work closely with cross functional team to align data science initiatives with business priorities
• Partner with leadership to identify and prioritize high impact opportunities for data science applications
• Present insights and recommendations through clear visualizations tailored for audiences across different roles and expertise levels

• Minium of 6 years building AI, Machine Learning and NLP solutions
• Minimum 3 years building applied AI/LLM and generative systems in production environments
• Bachelor’s degree in a relevant field such as Mathematics, Science, Engineering, or Computer Science
• Master’s Degree in relevant discipline preferred
• Strong programming skills in Python and experience building data and AI pipelines
• Experience with information retrieval, semantic search, or knowledge driven systems
• Exp…