Lead Software Engineer (Digital Supply Chain)

Quick Facts

• Role: Lead Software Engineer (hands-on technical leader)

• Focus: Agentic infrastructure and AI-powered workflow services for studio digital supply chain

• Work model: Hybrid (4 days onsite per week)

• Contract: 12 months, potential full-time conversion

Description

Lead the development of intelligent infrastructure for studio digital supply chain workflows. Productize AI prototypes into production-ready microservices, build event-driven services and reliable APIs, and design AI middleware and agentic workflows for mastering, localization, and delivery. You will also mentor engineers and collaborate with platform, product, and ML teams to deliver business-ready AI capabilities.

Responsibilities

• Translate AI prototypes into production-ready microservices using Java, Kotlin, Python, or TypeScript; deploy on Kubernetes and manage via CI/CD

• Build event-driven, loosely coupled services using Kafka or AWS event tools (SNS/SQS/EventBridge)

• Develop and maintain APIs with strong contracts, reliability, observability, and long-term maintainability

• Lead system design and delivery reviews; plan technical direction across engineering and product

• Partner with platform teams, product managers, and ML engineers to deliver AI capabilities

• Design and build API gateways, wrappers, and AI middleware for exposing studio systems and data to AI agents

• Manage secure access to tools, metadata, and content via Model Context Protocol (MCP)

• Deploy agentic workflow platforms (LangGraph/LangChain) for tool execution, context routing, and decision logic

• Implement tracing, audit logging, governance checkpoints (human approval, fallback paths) and integrate orchestration into media workflows

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, or related field

• 8+ years backend or systems engineering experience; at least 3 years building AI-powered or workflow-centric platforms

• Deep proficiency in Java or Kotlin and strong testing, observability, and systems-at-scale knowledge

• Structured communication and demonstrated technical leadership across cross-functional teams

• Production experience with AWS plus Docker and Kubernetes

• Hands-on infrastructure-as-code deployment experience (Terraform, CDK, or similar)

• Experience building or integrating workflow engines, ideally in LLM/GenAI contexts

Benefits

• 12-month contract with potential for full-time conversion

• Hybrid schedule with 4 days onsite per week