Like Google's own ambitions, the work of a Software Engineer goes way 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 a Software Engineering Manager in BigQuery’s Analytics AI organization, you will build the intelligent backbone and experiences for the next generation of data processing. You will build agents, skills, and tools that assist the entire data lifecycle; furthermore, you will be a key driver in building the surfaces and tools that make data development intuitive, fast, and seamless. You will collaborate with product managers, engineers, scientists, and designers to create unified, AI-accelerated agents and developer experiences that push the boundaries of how humans and AI collaborate on code and data.
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.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Design and develop next-generation agentic solutions and data developer experiences such as data ingestion, data pipelines, data science, feature extraction, model training, and more.
- Develop and maintain the technical roadmap of the team’s charter.
- Collaborate cross-functionally with Product, Data Scientists, Applied Scientists, and UX Designers and cross-teams to define the roadmap for AI-native data journeys.
- Iterate and enhance agentic frameworks by contributing to sophisticated tool-use, memory, context retrieval, multi-step orchestration, and evaluation (evals) to ensure accuracy and reliability of orchestration at petabyte scale.
- Lead the team on defining and executing on goal and long-term strategy.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience with Generative AI (Large Language Models, Multi-Modal Models) and Agentic Technologies (e.g., MCP, ADK, A2A, etc.).
- 2 years of experience in a people management or team leadership role.
- 1 year of experience building developer tools that improve developer velocity, code quality and code health (e.g., compilers, automated releases, code design and testing, test automation frameworks).
Preferred qualifications:
- Experience in building developer-facing products for integrated development environments (IDEs like VSCode) or Command Line.
- Experience with Large Language Models for code (e.g., Gemini, GPT-4, Claude), modern cloud infrastructure, and industry-standard developer tool frameworks.