Forward Deployed Engineer, Enterprise AI
Live Nation
- Location
- Beverly Hills, CA, USA
- Work model
- On-Site
- Level
- Mid
- Posted
- Sep 3, 2026
Skills
About this role
Job Summary
WHO ARE WE? Live Nation Entertainment is the world’s leading live entertainment company, comprised of global market leaders: Ticketmaster, Live Nation Concerts, and Live Nation Media & Sponsorship. Ticketmaster is the global leader in event ticketing with over 620 million tickets sold annually and approximately 10,000 clients worldwide. Live Nation Concerts is the largest provider of live entertainment in the world promoting more than 50,000 events annually for nearly 7,000 artists in 40+ countries. These businesses allow Live Nation Media & Sponsorship to create strategic music marketing programs that connect more than 1,200 sponsors with the 145 million fans that attend Live Nation Entertainment events each year. For additional information, visit www.livenationentertainment.com . WHO ARE YOU? Passionate and motivated. Driven, with an entrepreneurial spirit. Resourceful, innovative, forward thinking and committed. At Live Nation Entertainment, our people embrace these qualities, so if this sounds like you then please read on!
THE ROLE
Live Nation Entertainment is seeking a Forward Deployed Engineer – Enterprise AI to serve as a product and technical lead embedded with business stakeholders across the enterprise. This role reports directly to the Sr Director – Data & AI Engineering and is the bridge between business problems and production AI agents. The Forward Deployed Engineer combines business acumen, product thinking, and agentic AI technical capability into a single role. This leader will engage directly with senior business stakeholders to focus on high-impact AI use cases, then design, build, and ship production agents on the enterprise agentic AI stack — AWS Bedrock AgentCore, Amazon Bedrock, Databricks and associated control plane, governance & cybersecurity platforms. This role carries responsibility for measurable value delivery: taking AI opportunities from discovery through production deployment and adoption, ensuring alignment with enterprise architecture, security, and governance standards. The role owns the use case from discovery through first production release and adoption. It builds on the enterprise agentic AI platform but is not accountable for platform uptime or the shared-service AI roadmap, which sit with the Agentic AI Engineering team. Location: Los Angeles preferred, with approximately 20% travel. We will consider remote candidates across North America, with travel up to 50%. WHAT THIS ROLE WILL DO Business Engagement & Product Leadership Partner directly with business unit leaders to discover, scope, and prioritize AI agent use cases with clear ROI. Translate ambiguous business problems into well-defined agent products with success metrics. Present solutions, demos, and outcomes to executive audiences with clarity and confidence. Drive adoption: train users, gather feedback, and iterate rapidly toward measurable business value. Agent Engineering & Delivery Design, build, and deploy production AI agents on Amazon Bedrock AgentCore (Runtime, Gateway, Memory, Identity, Observability), Amazon Bedrock and Databricks, together with the associated control plane, governance and cybersecurity platforms. Develop tool integrations, MCP servers, RAG pipelines, and context engineering tailored to each use case. Define success metrics and build the evaluation harness for each agent — offline eval sets, rubric and LLM-as-judge scoring, regression gates in CI, and online quality monitoring of production traffic. Design for least-privilege agent identity, tool-scoping and guardrails from the outset, including defences against prompt injection and tool abuse, in line with Cybersecurity standards. Build with enterprise standards: Python, Terraform for infrastructure, GitHub and GitHub Actions for CI/CD. Ensure every deployed agent is secure, observable, cost-efficient, and supportable, in partnership with the Agentic AI Engineering team Enterprise Collaboration Work alongside Data