Senior AI Platform Governance Engineer

About the role

The work covers how AI systems are secured, audited and kept affordable at scale, spanning semantic models, deployment pipelines and cost visibility. It sits across sports, news, entertainment, film and digital teams.

At a glance

What you will do

• Build semantic models in Snowflake and Databricks so AI systems use agreed business definitions
• Create CI/CD pipelines and infrastructure as code for AI apps, agents and ML workloads
• Set up monitoring for latency, quality, reliability and model usage
• Define governance for models, agents, tools, datasets and APIs, with RBAC and policy enforcement

What they look for

• Degree in computer science or a related field, or equivalent experience
• Five or more years in data or cloud platform engineering
• Python, advanced SQL in Snowflake, AWS, semantic modelling and Git
• Hands on with Snowflake Cortex or Databricks Genie and Agent Bricks, plus frameworks like LangGraph, MCP and RAG
• Terraform or other infrastructure as code, and identity work with RBAC, IAM and Azure AD
• Docker and Kubernetes for model serving, and cloud cost allocation and tagging

Nice to have

• Five or more years with Snowflake, SnowPro certification a plus
• Five or more years with Databricks or Apache Spark
• Three or more years owning MLOps or AIOps pipelines
• CI/CD tooling such as GitHub Actions, Terraform and dbt, or LLM platform integration

Benefits

• Medical, dental and vision insurance
• 401(k) and paid leave
• Tuition reimbursement and other discounts