AI - Architect

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.  

Summary 

The AI Architect 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 architect intelligent systems that transform complex information into structured knowledge and actionable insights using modern AI, LLMs, machine learning, and generative approaches to solve complex business problems, while defining architectural patterns, technical standards, and integration approaches that enable scalable enterprise adoption and implementation. You will operate across the full lifecycle, from experimentation and evaluation to deployment and optimization, guiding system design and 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 and architecting applied AI systems that operate reliably in production environments, establish best practices, and deliver measurable business impact. 

Responsibilities

AI Architecture 

• Define and evolve reference architectures for AI, machine learning, and generative AI systems 

• Establish technical standards, patterns, and best practices for scalable and secure AI development 

• Guide platform decisions across data, model development, and deployment infrastructure 

• Evaluate and recommend tools, frameworks, and vendors aligned with long term architectural direction 

Development of AI Solutions

• 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 productionize generative AI solutions for real world use cases 

• Optimize systems for latency, cost, and throughput 

Evaluation, Reliability, and Quality 

• 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 

• Monitor deployed solutions and data pipelines for performance, stability, and data quality over time 

• Incorporate responsible AI practices including transparency, bias mitigation, and risk controls 

Collaboration and Communication 

• 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 

Required Capabilities 

• Minimum 10+ years building AI, Machine Learning and NLP solutions 

• Minimum 5+ years building applied AI/LLM and generative systems in production environments 

• Bachelor’s degree in a relevant field such Mathematics, Science, Engineering, or Computer Science. Master’s Degree in relevant discipline preferred 

• Experience designing enterprise scale AI and data architectures 

• Experience with real time and batch processing architectures 

• Strong programming skills in Python and experience building data and AI pipelines 

• Experience with information retrieval, semantic search, or knowledge driven systems 

• Experience with relational, non relational and semantic data stores 

• Strong software engineering fundamentals (APIs, system design, testing, version control) 

• Experience with Natural Language Processing methods and applications preferred 

• Familiarity with data privacy considerations and AI 

• Excellent analytical and problem solving skills 

• Demonstrated initiative and ownership of tasks and projects 

• Ability to prioritize, coordinate, and complete tasks to meet deadlines 

• Ability to work effectively both independently and in team environments 

• Ability to present complex problems in simple terms