Staff AI/ML Data Platform Architect

Google LLC; Sunnyvale (CA); Sur place; USD 207 000 - 300 000; Plein temps

Résumé du poste

Google LLC in Sunnyvale, CA is seeking a Staff Software Engineer for AI/ML on the AI Data Platform. You will design, build, and scale critical cloud lakehouse services processing exabytes of data for enterprise security workloads.

The role requires deep expertise in distributed systems, AI platforms, and large-scale data processing, with opportunities to guide technical direction across teams. In-person interviews are typical.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years designing, leading, and scaling large-scale software architectures, distributed systems, or high-throughput data processing platforms.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• Experience working with AI platforms or generative AI technologies (including generative AI agents).

Responsabilités

• Develop and optimize schema-on-read pipelines, inline streaming enrichment, and search indexing.
• Lead design and launch of cloud lakehouse solutions for enterprise customers.
• Improve architecture for scalable, modular data platforms and fast SQL analytics.
• Leverage SIEM, security data lakes, and large-scale data products to address customer needs.
• Manage priorities, communicate risks, and ensure timely delivery of projects.

Connaissances

Software development

AI platforms

Distributed systems

Formation

Bachelor's degree or equivalent practical experience

Outils

BigQuery

Cloud platforms

Data processing frameworks

Description du poste

Google LLC in Sunnyvale, CA is seeking a Staff Software Engineer for AI/ML on the AI Data Platform. You will design, build, and scale critical cloud lakehouse services processing exabytes of data for enterprise security workloads.

The role requires deep expertise in distributed systems, AI platforms, and large-scale data processing, with opportunities to guide technical direction across teams. In-person interviews are typical.