Engineering Manager - AI Compute Platforms Lead

Google LLC; Mountain View (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google LLC in Mountain View, CA is seeking a Share Engineering Manager for Google AI Compute. You will lead multiple software teams, shape technical direction, and deliver large-scale AI infrastructure projects across sites.

The role requires strong leadership, hands-on software engineering, and mentoring engineers while coordinating with product, research, and data science teams to scale systems and drive innovation in AI compute platforms.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 3 years of experience in a technical leadership role.
• 2 years of experience in a people management or team leadership role.
• Experience integrating generative AI tools or LLM interfaces into workflows.

Responsibilities

• Architect and evolves APIs and core runtime to support AI usage flows for Gemini and Antigravity.
• Scale infrastructure to maintain availability and sub-millisecond latencies at scale.
• Lead, grow, and mentor a team of software engineers, fostering a high-velocity culture.
• Define and enforce standards for code quality, testing, monitoring, and observability across services on the critical path.
• Collaborate cross-functionally with product, engineering, marketing, and data science teams to identify growth opportunities.

Skills

Bachelor’s degree or equivalent/prct.

8 years software development

3 years technical leadership

2 years people management

Generative AI / LLM integration

Education

Master's or PhD in CS or related field

Tools

Java

Spanner

ML inference

Job description

Google LLC in Mountain View, CA is seeking a Share Engineering Manager for Google AI Compute. You will lead multiple software teams, shape technical direction, and deliver large-scale AI infrastructure projects across sites.

The role requires strong leadership, hands-on software engineering, and mentoring engineers while coordinating with product, research, and data science teams to scale systems and drive innovation in AI compute platforms.