AI Systems & Memory Infrastructure Manager

Socket.dev; Sunnyvale (CA); On-site; USD 207,000 - 300,000; Full time

Job summary

Google’s AutoCloud team seeks engineers to design and implement agent memory systems, context synthesis pipelines, and hybrid search platforms for autonomous cloud agents.

You will mentor engineers, drive talent acquisition, and ensure privacy, availability, and efficiency across multi-tenant environments. This role emphasizes leadership, collaboration, and technical excellence in large-scale AI infrastructure.

Qualifications

• Bachelor's degree or equivalent practical experience required.
• 8 years of software development experience.
• 5 years leading ML design and optimizing ML infrastructure.
• 3 years in a technical leadership role.
• 2 years with GenAI techniques or related concepts.
• 2 years of people management or team leadership.

Responsibilities

• Define the technical roadmap and architecture for memory systems and context pipelines.
• Manage, mentor, and grow an engineering team; drive talent acquisition and performance evaluations.
• Lead design and implementation of memory caches, compression, and long-term knowledge stores for autonomous agents.
• Build automated evaluation pipelines to measure retrieval precision, memory recall, and grounding.
• Ensure multi-tenant data privacy, tenant isolation, and compliance across cloud memory subsystems.

Skills

Software development

ML design

Leadership

GenAI techniques

People management

Education

Bachelor's degree or equivalent

Master's or PhD in Engineering/CS

Tools

Vector databases

Embeddings

Knowledge graphs

Graph databases

Job description

Google’s AutoCloud team seeks engineers to design and implement agent memory systems, context synthesis pipelines, and hybrid search platforms for autonomous cloud agents.

You will mentor engineers, drive talent acquisition, and ensure privacy, availability, and efficiency across multi-tenant environments. This role emphasizes leadership, collaboration, and technical excellence in large-scale AI infrastructure.