AI Engineer
$130k - $160kWasserman Media
THE• TEAM operates at the epicenter of sports, music and entertainment, serving talent, brands and properties on a global scale. Headquartered in Los Angeles, THE• TEAM's presence spans 28 countries and more than 70 cities, including New York, London, Abu Dhabi, Amsterdam, Hong Kong, Madrid, Mexico City, Toronto, Paris and Sydney. For more information, please visit the.team Job Overview: The-Team is a culture-centric agency, serving the best athletes, artists, brands & properties in the world. We are seeking an AI Engineer - LLM Systems to help build the next generation of AI-powered systems and agents that transform how teams work across sports, media, talent, and brand consulting. This is a hands-on role focused on building real-world AI systems, not research. You'll design and deploy agent-based workflows, retrieval systems, and intelligent services that power internal tools and decision-making across the organization. If you've built AI systems that people actually use and want to shape how AI is deployed across an enterprise-we'd love to connect. What You'll Do:
Actual base salary is dependent on several factors including but not limited to; market dynamics, location and region, experience, specialized skills/training (education), level of responsibility, budgetary considerations, tenure at the company (for current employees), etc. The salary range listed is just one component of the total compensation package for employees. Compensation decisions are dependent on circumstances of each role
THE• TEAM does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.
- Design and build AI systems that can reason, retrieve information, and take action across enterprise tools and data sources
- Translate business use cases into structured workflows, defining task decomposition, tool usage, and input/output schemas
- Evaluate and prioritize AI use cases based on feasibility, data readiness, and business impact
- Define MVP scope and sequence development of AI systems based on prioritized use cases
- Develop and optimize LLM-powered systems, including prompt architectures, structured outputs, and multi-step reasoning workflows
- Build and scale retrieval pipelines (RAG) across structured and unstructured data (chunking, embeddings, ranking, hybrid search)
- Define how AI systems and workflows are orchestrated and structured, enabling reusable and composable capabilities as the platform evolves
- Build reusable AI services and APIs that power internal applications and automation
- Turn early prototypes into reliable, production-grade systems used by internal teams
- Evaluate and improve system performance across accuracy, latency, cost, and reliability in production environments
- 3-6 years of experience in s oftware engineering or applied AI, with a strong foundation in building production systems
- Strong proficiency in Python and experience building backend services and APIs
- Hands-on experience developing and deploying LLM-powered applications in production environments
- Experience implementing RAG pipelines, including document ingestion, chunking strategies, embedding workflows, and retrieval optimization
- Experience designing prompt architectures and structured outputs (e.g., JSON schemas, tool/function calling)
- Familiarity with building multi-step workflows or agent-like systems (not just single prompts or chat interfaces)
- Ability to take ambiguous business problems and translate them into structured AI workflows and systems
- Experience working with real-world data constraints (messy data, incomplete context, edge cases)
- Strong understanding of tradeoffs between accuracy, latency, and cost in LLM systems
- Demonstrated ability to ship quickly, iterate, and improve systems based on usage
- Experience building retrieval systems over large datasets (e.g., embeddings, semantic search)
- Experience designing multi-step AI workflows or integrating LLMs with tools, APIs, and data sources
- Experience working with unstructured enterprise data (documents, reports, transcripts)
- Experience integrating AI systems with APIs and enterprise tools
- Experience evaluating and improving LLM system reliability over time
Actual base salary is dependent on several factors including but not limited to; market dynamics, location and region, experience, specialized skills/training (education), level of responsibility, budgetary considerations, tenure at the company (for current employees), etc. The salary range listed is just one component of the total compensation package for employees. Compensation decisions are dependent on circumstances of each role
THE• TEAM does not discriminate on the basis of race, sex, color, religion, age, national origin, marital status, disability, veteran status, genetic information, sexual orientation, gender identity or any other reason prohibited by law in provision of employment opportunities and benefits.
Vacancy posted 1 day ago
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