À propos de ce poste AI Architect chez CAA
Job Description
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 Role
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
Partner with engineering teams to develop technology infrastructure
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
Qualifications
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
Location
This role is hybrid, based in our Nashville office.
Compensation
The annual base salary for this position is in the range of $213,000 - $240,000 in Nashville, TN. This position is also eligible for benefits and a discretionary bonus. Ultimately, the salary may vary based upon, but not limited to, relevant experience, time in the role, business sector, and geographic location, among other criteria. Please talk with a CAA Recruiter to learn more.
