Staff Software Engineer, Gemini Enterprise App, Cloud AI
As a Software Engineer on this team, you will design compliant pipelines managing massive datasets and transitioning raw log signals into real-time metrics. You will directly influence how our customers measure their AI investment and how our engineering teams validate their feature rollouts.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
- Define the multi-year architectural goal and technical roadmap for the Gemini Enterprise metrics ecosystem, aligning investments with broader Cloud AI product goals.
- Own critical design choices for high-throughput batch and streaming pipelines, translating highly ambiguous requirements into scalable and maintainable systems.
- Enforce strict SLAs/SLOs for production datasets and lead targeted investments to optimize cloud infrastructure costs, automate toil, and drive incident postmortems.
- Act as the primary engineering liaison to Data Science, Product, and Engineering leaders to align project timelines and build the telemetry needed to measure product quality.
- Foster a high-performing team culture through active mentoring, while advocating Google-wide standards in data privacy, security compliance, and testing.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience programming in C++, Java, Python, Kotlin or Go.
- 5 years of experience testing, and launching software products.
- 3 years of experience with software design and architecture.
- Experience integrating generative AI tools or LLM interfaces into workflows.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience with internal Google-scale distributed data technologies and pipeline frameworks (e.g., Flume, Dream-pipe, Conduit, or SQL Pipelines) to build data warehousing solutions, analytics APIs, or customer-facing dashboards.
- Experience with delivering concise, technical updates, architectural trade-offs, and engineering recommendations to executive leadership and cross-functional stakeholders.