AI Engineer

Job not on LinkedIn

🕒 April 10

🏄 California, New York – Remote

🏄 California – Remote 🗽 New York – Remote

💵 $130k - $160k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 AI Engineer

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Wasserman

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2002

⚽ Sports

Sports • Entertainment • Marketing

Wasserman is a global company operating at the intersection of sports, music, entertainment, and culture. With its headquarters in Los Angeles and a presence in 28 countries, Wasserman serves talent, brands, and properties worldwide. The company is involved in talent representation, marketing, live events, and brand partnerships, managing major events and providing hospitality services. Wasserman is known for its comprehensive approach to sports and media, working with talents in various fields such as baseball, basketball, and global football. The company also engages in music and entertainment by partnering with artists. It is a significant player in enhancing brand experience through innovative marketing strategies and events.

📋 Description

• 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

🎯 Requirements

• 3–6 years of experience in software 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

🏖️ Benefits

• Bonus potential if applicable for role