Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
- 1 year of 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), or specialization in another ML field.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
- Experience with generative AI agents and working with cross-functional teams.
Preferred qualifications:- Master's degree or PhD in Computer Science or related technical fields.
- Experience building with Large Language Model (LLM) orchestration frameworks.
- Experience with LLM concepts, including prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation techniques.
- Experience developing accessible technologies.
About the jobThe 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: $147000 - $211000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities- Execute experiments to vet emerging AI capabilities and determine their internal product-market fit.
- Deploy and maintain production-grade AI agents capable of reasoning, tool-use, and multi-step task execution.
- Manage the full lifecycle of your code, from initial prompt engineering and fine-tuning to Continuous Integration/Continuous Deployment (CI/CD) and real-time monitoring of agent performance.
