Senior AI Platform Governance Engineer

NBCUniversal•New York, NY

6d•$115,000 - $145,000•Remote

About The Position

NBCUniversal is building the foundation for responsible, scalable AI across its media and entertainment portfolio. The Senior AI Governance Engineer will help define how AI products are governed, secured, monitored, and operationalized across sports, news, entertainment, film, and digital businesses. The role designs and maintains semantic models in Snowflake and Databricks, partners with data owners and engineering teams to establish governed metrics, entities, lineage, and access patterns, and builds CI/CD pipelines and Infrastructure-as-Code solutions for AI applications, agents, semantic models, and ML workloads. It enables repeatable deployment across development, staging, and production; creates monitoring frameworks for latency, quality, reliability, model usage, and AI operational health; and defines standards for auditability, compliance, and responsible AI adoption. The role also optimizes AI infrastructure and cloud consumption, provides visibility into model, agent, and inference costs, designs governance frameworks for models, agents, tools, datasets, and APIs, and implements role-based access controls, identity controls, and policy enforcement across AI platforms. This position is fully remote and eligible for company-sponsored benefits. The stated salary range is $115,000–$145,000 per year. Applications are accepted on an ongoing basis.

Requirements

Bachelor's degree in computer science or a related discipline, or equivalent.
At least 5 years of experience in data or cloud platform engineering.
Experience coding in Python and advanced SQL (Snowflake), and experience with AWS, semantic modeling, and Git.
Experience with AI and databases, such as Snowflake Cortex or Databricks Genie/Agent Bricks.
Ability to understand how AI frameworks work, including LangGraph, MCP, and RAG.
Experience with Terraform or other Infrastructure-as-Code for cloud AI environments.
Experience with security and identity, including RBAC, IAM policies, and Azure AD.
Experience with AI FinOps, including cloud cost allocation, tagging, and optimization.
Experience with Docker and Kubernetes for containerization, model serving, and orchestration.
Excellent communication and presentation skills.

Nice To Haves

SnowPro Core or Advanced certification preferred.
At least 5 years of experience in Snowflake.
At least 5 years of experience in Databricks or Apache Spark.
At least 3 years of experience owning MLOps/AIOps pipelines.
At least 3 years of experience with CI/CD tooling such as GitHub Actions, Terraform, and dbt.
At least 1 year of experience integrating LLM or generative AI platforms.

Responsibilities

Design and maintain semantic models in Snowflake and Databricks so AI systems use trusted business definitions.
Partner with data owners and engineering teams to define governed metrics, entities, lineage, and access patterns.
Build CI/CD pipelines and Infrastructure-as-Code solutions supporting AI applications, agents, semantic models, and ML workloads.
Enable repeatable deployments across development, staging, and production environments.
Create monitoring frameworks for latency, quality, reliability, model usage, and AI operational health.
Define standards for auditability, compliance, and responsible AI adoption.
Optimize AI infrastructure utilization and manage cloud consumption across Snowflake, Databricks, and supporting services.
Develop visibility into model, agent, and inference costs to support sustainable AI growth.
Design governance frameworks for models, agents, tools, datasets, and APIs.
Implement RBAC, identity controls, and policy enforcement across AI platforms.