Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
The Google Cloud AI Research team addresses AI challenges motivated by Google Cloud’s mission of bringing AI to tech, healthcare, finance, retail and many other industries. We work on a range of unique problems focused on research topics that maximize scientific and real-world impact, aiming to push the state-of-the-art in AI and share findings with the broader research community. We also collaborate with product teams to bring innovations to real-world impact that benefits our customers.
Responsibilities
- Lead the engineering roadmap to transform the Hub into the definitive repository for all Artificial Intelligence (AI) Assets, including Application programming interfaces (APIs), Model Context Protocol (MCP) Servers, and Agents.
- Drive technical integrations with API Gateways for automated cataloging and with Google Cloud Platform (GCP) Agent Cloud for downstream consumption.
- Recruit and mentor performing engineering team, promoting a culture of technical excellence in cloud-native and AI-integrated systems.
- Provide architectural guidance and conduct design reviews for distributed systems, ensuring platform reliability and performance.
- Partner with Product and Leadership across Apigee and GCP to ensure the Hub remains important to the organization's digital and Agentic strategy.
Qualifications
Minimum qualifications:
- Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
- 8 years of experience with architecting and developing distributed software systems or cloud-native infrastructure.
- Experience with managing engineering teams.
Preferred qualifications:
- Experience with shipping enterprise-grade products or platforms within a large-scale cloud environment.
- Experience with Large Language Model (LLM), Generative AI and Agentic Artificial Intelligence (AI).
- Experience with Generative AI Agent and Large Language Model development.
- Ability to communicate technical roadmaps and architectural decisions to engineering teams and non-technical stakeholders.