Software Engineering Manager, AutoCloud, Agentic AI Systems

• Manage, mentor, and grow a team of software engineers. Conduct 1:1, support career, manage performance, foster culture, and lead recruiting and hiring initiatives. Cultivate a psychologically safe, transparent, and high-velocity team environment that thrives on continuous learning, innovation, and customer-first focus.
• Lead end-to-end engineering execution across multi-quarter roadmaps—ensuring timely delivery of scalable, secure, and production-ready agentic systems and customer user journeys.
• Partner with Product Management, UX, and Technical Leads to translate business goals into clear technical milestones, sprint plans, and effective resource allocation.
• Build strong partnerships with Engineering Managers, Directors across Google Cloud to resolve cross-team dependencies and drive joint technical deliverables.
• Advocate high standards for code quality, architectural reviews, CI/CD, system availability, on-call health, and LLM evaluation/benchmarking methodologies.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
  
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
• 2 years of experience in a people management or team leadership role.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
• 3 years of experience working in a complex, matrixed organization.
  
• Experience building multi-tenant architectures with strict access control, tenant isolation, and data governance standards.
• Proven experience designing agent memory systems (short-term/working memory, episodic/semantic memory), context caching (e.g., Gemini context caching), context compression/summarization, vector databases/embeddings, and knowledge graphs.
• Deep background in Information Retrieval (IR), hybrid search (semantic + lexical), graph data stores, and aggregating complex distributed state (logs, metrics, IAM, infrastructure topology).

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
  
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 3 years of experience in a technical leadership role.
• 2 years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).
• 2 years of experience in a people management or team leadership role.