Principal AI Engineer

Lead the design, development, and delivery of intelligent software systems combining enterprise architecture, full-stack engineering, data science, and machine learning. Build production-grade AI platforms and products that support critical workflows, decision-making, automation, and business insight.

Responsibilities

• Lead machine learning, statistical, and AI-driven solution development.
• Own end-to-end delivery of AI-enabled products from problem framing through deployment and monitoring.
• Evaluate machine learning, analytics, and natural language processing approaches.
• Build robust pipelines, reusable services, and scalable production AI environments.
• Design secure, cloud-native applications and backend services integrating AI and enterprise workflows.
• Lead full-stack engineering across backend services, web applications, APIs, data models, and integrations.
• Architect microservices, event-driven systems, and managed cloud services for reliability and scalability.
• Provide architectural leadership for enterprise and third-party integrations.
• Productionize AI and machine learning systems using MLOps practices.
• Establish standards for testing, deployment, observability, drift detection, retraining, and documentation.
• Serve as a hands-on technical leader and mentor engineers.
• Define technical strategy, lead cross-functional initiatives, and communicate complex trade-offs to stakeholders.

Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience.
• 10+ years of experience in software engineering, applied machine learning, data science, or related fields.
• Strong expertise in backend development, APIs, scalable system design, and full-stack development.
• Proficiency in Python and SQL.
• Experience with scikit-learn, TensorFlow, PyTorch, or similar machine learning frameworks.
• Strong experience with AWS, Azure, or GCP and cloud-native systems.
• Experience with Snowflake, BigQuery, or Databricks.
• Familiarity with Infrastructure as Code, microservices, and event-driven architectures.
• Strong grounding in statistics, experimentation, and analytical methods.
• Experience deploying and maintaining production AI/ML systems, including monitoring and governance.
• Understanding of secure system design, data privacy, and enterprise engineering practices.
• Excellent communication, stakeholder influence, mentorship, and technical leadership skills.
• Experience in media, entertainment, or similarly fast-paced industries is a plus.

Benefits

• Opportunity to work at a leading global entertainment company.
• Access to tools, leadership, and resources to create and drive a center of excellence.
• Opportunity to do the best work of your career.
• Inclusive and diverse company culture.
• Competitive programs supporting employee well-being.
• Collaborative environment with room to grow.