Software Engineering Manager II, AI Productivity
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Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience in software development.
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
- Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 3 years of experience working in a complex, matrixed organization.
- Experience building application layers with LLMs, prompt engineering, agentic platforms (e.g., LangChain, ADK/Orcas), vector search, or semantic embeddings.
- Experience or deep interest in AI evaluation, model quality assurance, automated red-teaming, or software verification frameworks.
About the job
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.
As the Engineering Manager for the AI Productivity team you will lead a highly AI-focused team, working on two of Google's flagship internal AI productivity products: go/sqlminer and go/agentflux.
In this role, you will split your time between technical contribution, building solutions and people/project management, bringing a "builder" mindset. You will guide the team's career growth while helping architect, design, and prototype solutions at the intersection of Generative AI, SQL pipelines, and AI agent evaluations.The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.
Responsibilities
- Collaborate with local Brazilian engineering teams as well as global cross-functional AI Productivity, Developer Platforms, and Safety/Security teams to align on roadmap priorities and deliver end-to-end agentic capabilities.
- Establish clear expectations with individuals based on their level and role, aligned to the broader organization's goals, meet regularly to discuss performance and development and provide feedback and coaching.
- Maintain a strong presence by building solutions, participating in technical design, and conducting code reviews, while helping the team navigate the non-deterministic nature of LLM systems.
- Drive the roadmap for integrating advanced LLM capabilities (e.g., multimodal, agent tools, Simula synthetic data generation) into internal SQL engines, ensuring low-latency and cost-effective execution.
- Evolve the automated agent evaluation pipeline by expanding tool profiling and enhancing the automated red-team auditing to ensure mutating operations are safely caught and mocked.
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