AI Platform Engineer
Build and govern the cloud data infrastructure that powers AI skill mining, including BigQuery, storage, IAM, Vertex AI pipelines, and automated data workflows. The role partners with AI, data science, and product teams to deliver observable, privacy-conscious infrastructure.
About the job
Responsibilities
- Own the data infrastructure layer supporting AI skill mining, including BigQuery datasets and schemas, cloud storage, service accounts, IAM, Vertex AI pipeline infrastructure, Dataform integration, and event-streaming resources.
- Build automated data pipelines, scheduled jobs, data-copy pipelines, and backfill orchestration.
- Learn the data infrastructure landscape with support from a peer and manager before taking independent ownership.
- Ship infrastructure changes such as datasets, storage resources, IAM policies, and schema updates.
- Own core data infrastructure, including preprocessing storage buckets, service accounts, and access policies across environments.
- Partner with AI and data science engineers to provision governed infrastructure for new pipeline and data needs.
- Contribute to data-quality checks, freshness monitoring, and anomaly detection.
- Strengthen infrastructure-as-code practices and CI/CD.
- Expand the data platform as the team grows into new channels, customer segments, and verticals.
- Own data governance, including retention, anonymization, opt-out handling, and access separation for privacy-sensitive content.
- Partner with AI, backend, product, and analytics teams on reliable data contracts and predictable infrastructure.
Requirements
- Strong experience in data engineering, data platform, or data-focused infrastructure work.
- Deep familiarity with BigQuery or a comparable cloud data warehouse, including schema design, dataset management, and access governance.
- Hands-on infrastructure-as-code experience and the ability to provision cloud resources.
- Understanding of data contracts, freshness, lineage, quality, and downstream dependencies.
- Experience implementing retention policies, anonymization, and access separation for privacy-sensitive data.
- Ability to turn ambiguous data needs into concrete, durable infrastructure plans.
- Focus on observability through measurement and monitoring.
- Comfort working on a distributed team and communicating asynchronously.
Compensation and Benefits
- Competitive salary.
- Comprehensive benefits and perks.
- Opportunities for growth and training.
- Access to AI tools and inclusive office environments.
Skills
BigQuery, Terraform, GCP, Vertex Ai, Dataform, IAM, CI/CD, Data Warehousing, Data Governance, Data Quality, Event Streaming, Cloud Storage, Service Accounts
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