Engineering Manager leading Warner Music Group’s Forward Deployed Engineering team. Driving secure AI automation, reusable tooling, and business-unit delivery across the music company.
Responsibilities
Lead, coach, hire, and manage a high-performing Forward Deployed Engineering team
Embed engineers in business units while maintaining centralized technical standards and reporting
Define and maintain the FDE technical operating playbook, including intake standards, routing rules, reusable delivery models, and engagement lifecycle
Create repeatable frameworks for intake routing, priority rubrics, and graduation gateways
Align engineers, product owners, business sponsors, and executive partners around technical standards, priorities, and roadmaps
Promote reusable assets, developer tooling, ADK/SDK patterns, internal asset marketplaces, and best practices
Set technical standards for AI agents and automation using enterprise frameworks including Databricks, Gemini Enterprise, Claude, and Airtable
Own security, compliance, Cost of AI telemetry, and lifecycle management from prototype through production or retirement
Translate business pain points into technical requirements and educate business units on working with technology
Report FDE capacity, outcomes, and aggregate AI costs to leadership
Define success metrics and operate intake SLAs, reuse, and outcomes as demand scales
Report to the Director of FDE & AI Optimization and partner with Data Engineers, Product Owners, and business sponsors
Requirements
7+ years of experience in software engineering, solution architecture, data engineering, or AI/ML delivery
2+ years managing engineers
Experience leading teams in a Forward Deployed Engineering, technical consulting, or heavily matrixed environment
Experience defining, scaling, and maintaining operational playbooks, intake standards, routing, and reusable delivery models
Ability to transform ambiguous processes into clear, repeatable frameworks
Experience championing reusable assets, developer tooling, ADK/SDK patterns, and best practices
Experience owning operational governance across the delivery lifecycle, including compliance, cost telemetry, and production graduation
Deep familiarity with modern LLM ecosystems, agentic workflows, and cloud data platforms such as Databricks, Gemini, Claude, and Cursor
Ability to distinguish short-term optimization opportunities from initiatives requiring a product roadmap
Exceptional written and verbal communication skills
Experience measuring engineering ROI and managing vendor, licensing, or infrastructure costs in production
Experience rolling out intake and routing models in matrixed enterprises
Hands-on delivery of agents, automation, or internal platforms on Databricks, Gemini Enterprise, Claude, Airtable, and/or Cursor
Experience establishing reuse paths and production ownership standards
Music, media, or entertainment industry experience is an additional qualification
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