Senior Software Engineer, Core, engEDU

Google•New York, NY

About The Position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward. The Core Engineering Education team will transform how Googlers build by embedding AI into our curriculum and delivering training directly into work. We’ll lean on the strong collaboration with hero early adopters to upskill all our talent for Google’s next era of innovation. In this role, you will execute technical tasks to develop specialized AI agents and next-generation UI components that facilitate seamless human-agent interaction and effective in-the-flow learning. Working closely with other team members, you will deliver high-quality, testable code across full-stack surfaces that power the productivity of Google's Software Engineers. This is a unique opportunity to expand your expertise while helping transition Google's work paradigm from manual task execution to agentic orchestration. 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.

Requirements

Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Experience working with AI agents and genAI-native architectures.

Nice To Haves

Master's degree or PhD in Computer Science, or a related technical field.
1 year of experience in a technical leadership role.
Experience building productivity platforms, or enterprise software at scale, with a strong intuition for how to elegantly merge Human-Computer Interaction (HCI) with autonomous AI.
Experience designing, orchestrating, safely evaluating, and deploying autonomous AI agents, coding assistants, or complex multi-agent systems.

Responsibilities

Build and enhance core features of Google's primary agentic learning tools ensuring the platform is reliable, high-performing, and intuitive for hundreds of thousands of Google Software Engineers.
Execute tactical subtasks to build and refine AI agents through supporting automated workflows for application scaffolding, release debugging, and production triage.
Contribute to the development of next-generation UI components, enabling agents to present rich, interactive, and context-aware interfaces to developers and other users.
Deliver high-quality, well-factored, and testable code across full-stack surfaces, incorporating feedback from executive team members to ensure the resilience and maintainability of our developer-facing systems.
Collaborate with cross-functional partners to identify and automate manual engineering toil, improving Product Feature Velocity (PFV) for both traditional inner-loop development and the emerging intent-driven SDLC.