AI Performance & Reliability Engineer II

The Walt Disney Company; New York (NY); On-site; USD 125,000 - 167,000; Full time

Job summary

The Walt Disney Company is hiring a Software Engineer II - AI Performance in New York, NY. You will design and build data pipelines and evaluation frameworks to assess the real-world performance and impact of Disney’s AI and observability tools across streaming and media platforms.

You will partner with SRE, product, and platform teams to reduce alert fatigue, quantify model drift, and deliver clear metrics that drive leadership decisions.

Qualifications

• 3+ years of backend and data pipeline engineering experience.
• Strong experience with data platforms and distributed processing tools (PySpark, SQL, Pandas).
• Understanding of model evaluation concepts (precision, recall, drift).
• Experience with modern dev practices (GitHub, Docker, AWS/EKS).
• Proficiency with AI-assisted development tools (Cursor, Claude Code).
• Ability to translate telemetry into reliability metrics and business insights.

Responsibilities

• Design, build, and maintain automated data pipelines and APIs.
• Develop evaluation frameworks to track model precision, recall, and drift.
• Link AI outputs to incident lifecycles and business impact metrics.
• Create dashboards for AI ROI, operational health, and performance narratives.

Skills

Backend and data pipelines

Model evaluation concepts

Analytical skills

Cross-functional collaboration

AI-assisted development

Education

Bachelor’s degree in CS/Engineering or equivalent

Tools

PySpark

SQL

Pandas

Databricks

Snowflake

GitHub

Docker

AWS/EKS

Cursor

Claude Code

Job description

The Walt Disney Company is hiring a Software Engineer II - AI Performance in New York, NY. You will design and build data pipelines and evaluation frameworks to assess the real-world performance and impact of Disney’s AI and observability tools across streaming and media platforms.

You will partner with SRE, product, and platform teams to reduce alert fatigue, quantify model drift, and deliver clear metrics that drive leadership decisions.