Technical Lead, Vector Search - Vertex AI

Google Cloud's software engineers develop next-generation technologies that change how billions of users connect, explore, and interact with information and one another. The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services and Google Cloud. Their global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience building and developing infrastructure, distributed systems or networks, or experience with compute technologies, storage, or hardware architecture.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.

Nice to have:

• Master’s degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience.
• 8 years of experience with data structures and algorithms.
• 3 years of experience working in a complex, matrixed organization including technical leadership role leading project teams and setting technical direction.
• 3 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling, computer vision).

• Own the technical goal and architecture of the Vector Search Serving infrastructure and drive decisions that ensure the system can manage massive datasets and query volumes with low latency.
• Contribute to critical code paths, conduct high-quality code reviews, and author technical design documents to maintain a technical presence.
• Manage, mentor, and grow a team of software engineers.
• Advocate for reliability and service health by overseeing incident management processes, ensuring that customer issues are resolved effectively and that post-mortems lead to systemic improvements.
• Act as the bridge between technology and users by understanding customer use cases and ensuring the infrastructure evolves to meet their changing needs.