Software Engineer, Agentic AI and LLMs, Google Ads

Google•Irvine, CA

4h•$147,000 - $210,000

About The Position

Google Ads is building intelligent, autonomous systems with conversational and agentic workflows that resolve complex advertiser inquiries across chat, email, and virtual meetings. The team connects frontier foundation models with large-scale distributed infrastructure to create reliable, helpful, and safe enterprise assistants, applying machine learning and generative AI models such as Gemini to support a global business. As a software engineer at Google, you will develop technologies and systems that operate at massive scale. You will work on a project important to Google’s needs, with opportunities to work across the full stack and take on new problems as business priorities evolve. The work focuses on building and optimizing backend services, storage schemas, APIs, data pipelines, and specialized machine-learning solutions. It also involves collaboration on technical design and code reviews, maintaining documentation, and resolving production issues. The role contributes to systems intended to protect users, improve ad quality, and optimize advertiser campaign return on investment.

Requirements

Bachelor’s degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
At least 2 years of software development experience in one or more programming languages such as Java, Python, Go, or C++, or 1 year of experience with an advanced degree.
At least 1 year of experience in one or more of the following: speech/audio systems, reinforcement learning (sequential decision making), ML infrastructure, or a distinct specialization in another machine-learning field.
At least 1 year of end-to-end machine-learning experience, including model deployment, model evaluation, data processing, and debugging.

Nice To Haves

Master’s degree or PhD in Computer Science, Computer Engineering, Machine Learning, or a related technical field.
At least 2 years of experience with data structures or algorithms in an academic or industry setting.
At least 1 year of experience with LLMs, prompt design or optimization (e.g., APO), or modern agentic orchestration frameworks.
Experience developing accessible technologies that comply with global usability and accessibility standards.
Experience with full-stack development across back-end services, database schemas, APIs, and front-end frameworks such as Dart, JavaScript, or TypeScript.

Responsibilities

Write product or system development code using Java, Python, Go, or C++ to build and optimize high-throughput backend services, storage schemas, APIs, and data pipelines for massive-scale GenAI systems.
Collaborate with peers and stakeholders through technical design and code reviews, promoting best practices in style, code checking, accuracy, testability, and efficiency.
Contribute to technical documentation or educational developer content and adapt engineering specifications based on system or program updates, prompt-engineering variations, and internal and external user feedback.
Triage issues and debug, track, and resolve production anomalies by analyzing causes and impacts on hardware, network or service operations, system latency, and output quality.
Implement solutions in specialized machine-learning areas using ML infrastructure, contributing to model optimization, data processing, and Tier 2 on-call reliability.