onsite
Staff Software Engineer, Server AI Foundations - Google
Software Engineer
We're looking for a Software Engineer focused on designing and building scalable technical solutions. This lead role requires 8+ years of relevant experience.
About the role
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 Large Language Model (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.
- 1 year of production experience on Generative AI (GenAI)/Retrieval-Augmented Generation (RAG)/Agents or agentic frameworks.
- Experience building upon, contributing to an internal development platform, worked on the developer experience and velocity.
Responsibilities
- Lead the design, architecture, and development of complex, robust, and AI-powered tools and features for our internal production platform infrastructure. Ensure systems are highly scalable, reliable, and performant.
- Influence and coach a distributed team of engineers.
- Forge strong partnerships to define, architect, and deliver impactful AI-integrated solutions that enhance developer productivity and align with the strategic objectives.
- Identify and lead strategic initiatives for AI investment. Drive the roadmap for AI features that transform code generation, automated testing, large-scale change capabilities, and overall developer productivity within Google's ecosystem.
- Design, develop, test, deploy, maintain, and enhance large-scale software solutions. Anticipate and address complex issues within the AI-motivated ecosystem at an architectural level. Lead efforts to design and implement sustainable, long-term solutions.