Software Engineer, AI Infrastructure, Core

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 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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

• Design, write, and deploy production-grade code for multi-agent workflows, tool-use orchestration engines, and dynamic decision-making pipelines.

• Deploy AI frameworks and tools, to enable velocity in product development and scalability of agentic applications that require high-precision and safe execution under complex real-world conditions.

• Build robust, high-throughput model serving pipelines and real-time execution environments optimized for latency, reliability, and scale.

• Integrate continuous, data-driven feedback loops into AI development methodologies. Construct automated testing, continuous evaluation, and observability frameworks to assess agent coverage, monitor regressions, and safeguard product quality across end-to-end workflows.

• Adopt and integrate distributed tracing, data lineage architectures, and telemetry (e.g., OpenTelemetry) into high-volume generative AI data pipelines.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.