Software Engineering Manager, AutoCloud, Context and Memory

Software Engineering Manager, Auto Cloud, Context and Memory

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile;

the list goes on and is growing every day.

Auto Cloud is Google Cloud's autonomous, AI-powered cloud management portfolio. We are transforming how enterprise customers design, deploy, operate, investigate, and optimize their workloads and infrastructure across GCP. Autonomous agents are only as capable as the context and memory they operate on. The Auto Cloud Context and Memory team is responsible for the core cognitive backbone that powers Auto Cloud agents: managing short-term dynamic context, long-term episodic and semantic memory, cloud topology graphs, context caching, and intelligent retrieval across petabyte-scale cloud logs, metrics, configurations, and historical runbooks.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits.

• Define the technical roadmap and architecture for agent memory systems, dynamic context synthesis pipelines, graph-based cloud representations, and hybrid search/RAG platforms.
• Manage, mentor, and grow an exceptional team of software engineers.
• Drive talent acquisition, foster an engineering culture, conduct performance evaluations, and support career progress.
• Lead the design and implementation of low-latency context caching, token compression/pruning strategies, working memory buffers, and long-term episodic knowledge stores for autonomous agents.
• Build automated evaluation pipelines and benchmarking frameworks to measure and optimize context retrieval precision, memory recall, grounding fidelity, and hallucination reduction.
• Ensure all memory and context subsystems adhere to the highest standards of multi-tenant enterprise data privacy, tenant isolation, compliance, high availability, and operational efficiency.
• Partner with Auto Cloud agent orchestration teams, and GCP service teams to seamlessly integrate cloud state into agent context.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law.