Senior Software Developer, Applied AI, Commerce AI

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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.

In this role, your mission is to become the operational backbone for modern commerce, empowering brands from design partners to mid-market retailers to own their customer relationships through intelligent, multimodal AI agents.

You will leverage Gemini to build a "flywheel" of sales and support capabilities that drive conversion and efficiency. You will build the foundational systems that allow these agents to scale globally, ensuring a rapid, "out-of-the-box" onboarding experience for merchants and enabling a seamless headless implementation for those who prefer to own the user experience (UX).
The Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for Customer Experience (Shopping Agent, CX Agent Studio, Agent Assist, Vertex AI Search - Commerce, Customer Experience Insights), along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders with unprecedented speed. Join us to work on cutting-edge projects and shape the future of AI in a fast-paced, collaborative, and impactful environment.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 (https://www.google.com/about/careers/applications/benefits/).

Minimum qualifications:

- Bachelor’s degree or equivalent practical experience.

- 5 years of experience with software development in C++ or Python.

- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.

- 3 years of experience with Large Language Models and evaluation frameworks.

- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).

Preferred qualifications:

- Master's degree or PhD in Computer Science or related technical field.

- Experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.

- Experience building and scaling platform infrastructure for SaaS or e-commerce products.

- Ability to work in an agile, "0-to-1" environment, driving projects from conception to launch with the ability to take initiative.

- Excellent product sense with a focus on developer experience (DX) and merchant tooling, ensuring features directly address customer pain points.

- Build robust self-service tooling and automated evaluation frameworks, utilizing Large Language Model (LLM) simulators and judges to continuously monitor performance, manage quality hill-climbing, and prevent regressions.

- Architect and refine unified, scalable APIs for critical functions like catalog ingestion (e.g. Universal Commerce Protocol), real-time agent configuration, and "one-line SDK" site integration.

- Design infrastructure that shrinks the onboarding gap, enabling rapid deployment for a global customer base ranging from large enterprises to Shopify merchants.

- Drive the feature life-cycle from experimentation to production, ensuring high reliability for complex shopping journeys that combine search, sales, and support.