Lead Developer, AI Workflows & Media Supply Chain

The Original Content Services group part of Apple Services focuses on creating the premiere video experience for all content types with impact throughout the industry for a worldwide digital audience. The team brings together expertise in Partner Relations TV App Services Video Services Technical Operations and Quality Control to support that looking for a Lead Developer AI Workflows u0026 Media Supply Chain to join our Integration and Technology team. This role is centered on building and maintaining the software systems that automate our media supply chain including title and asset management metadata curation archival policy system governance technical workflow improvement and distribution standardization with AI/ML applied with the same engineering discipline testing and accountability expected of any production system. Were looking for someone who is passionate about building scalable media supply chain workflows and can contribute to a diverse organization.n

The Lead Developer AI Workflows u0026 Media Supply Chain will support the following:nnDesign build and maintain AI/ML-driven automation and agentic workflows that streamline ingest metadata enrichment QC asset validation and downstream distribution across the media supply AI models and internal data systems by deploying secure scalable interfaces (e.g. Model Context Protocol (MCP) servers) and robust API integrations with Media Asset Management (MAM) inventory and metadata platforms. nnBuild automated validation loops and human-in-the-loop review systems to ensure AI-generated metadata and decisions meet accuracy compliance and auditability standards before hitting systems of build and maintain internal tools (dashboards UIs CLI utilities) that give operators visibility into and control over autonomous AI-driven with AI/ML developers to determine where AI/ML genuinely improves supply chain efficiency versus where deterministic automation is the better processes to detect reconcile and resolve data and workflow inconsistencies across the media supply chain ensuring outputs consistently meet Apples delivery and deploy targeted automation scripts micro-services and workflows to resolve emerging bottlenecks in content ingest QC and delivery as a technical lead and review for other engineers working on supply chain and automation initiatives and represent the teams technical direction to cross-functional multiple concurrent priorities and adapt to shifting requirements in a fast-changing production or review the work of other engineers and incorporate differing technical perspectives into technical decisions.n

We are looking for experienced professionals who have built and operated production automation or AI/ML systems within the media entertainment or technology industries. nnBachelors degree in Computer Science Engineering or a related technical field or equivalent practical experience.n5 years of experience as an automation and workflow designing and shipping automated end-to-end workflows (e.g. ingest metadata enrichment QC delivery) that measurably reduced manual effort or turnaround applying AI/ML or LLM-based automation to production systems beyond programming in Python and SQL to build automation integrations or data working with professional media file formats and QC/delivery standards used in streaming or entertainment writing tested maintainable production code and following standard software engineering practices (code review version control CI/CD).nDirect experience handling sensitive and confidential information with integrity and to be onsite; this role is an in-person onsite to work some nights and weekends as to 10% travel required; both domestic and international.n

Experience building or operating secure API layers (e.g. MCP servers) that give AI agents standardized access to order or asset management with Retrieval-Augmented Generation (RAG) or metadata indexing techniques for querying large-scale content with workflow orchestration (e.g. Airflow Temporal) message queuing (e.g. Kafka SQS) and containerized deployments (Docker/Kubernetes).nExperience building human-in-the-loop review processes to validate automated or AI-generated outputs before they reach systems of with JavaScript/TypeScript and shell scripting to build internal tools such as dashboards or CLI utilities. nExperience communicating technical trade-offs to non-technical partners and adjusting a technical direction based on their input.n