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 ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). 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), ML infrastructure, or specialization in another ML field. Experience with core GenAI concepts (e.g., LLM, Multi-Modal, Large Vision Models) and text, image, video, or audio generation. Preferred qualifications: Master's degree or PhD in Computer Science or a related technical field. 2 years of experience with data structures and algorithms. Experience in solving customer problems by navigating ambiguous requirements to deliver effective technical solutions and tangible business outcomes. Experience in Vertex AI, BigQuery, Cloud Storage, Dialogflow. Experience in prompt development, model evaluation, and the creative application of Artificial Intelligence (AI). Ability to be flexible and resilient in dynamic environmentsto take ownership and respond to urgent business or customer issues. About the job 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, you will be at the forefront of applying Google's Generative AI to solve real-world issues for our customers. You will act as a specialized software developer embedded with key accounts, working to build, deploy, and optimize sophisticated AI agents on our customer engagement suite (CES) platform. You will bridge the gap between our core product engineering teams and customer needs, directly accelerating customer success and shaping the future of our AI products. 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. Responsibilities Partner directly with select, customers to understand their business issues. Design, co-develop, debug, and deploy custom conversational AI agents and solutions to accelerate their time to value. Act as a high-level problem solver, empowered to write bespoke code, develop custom tooling, and contribute directly to the core product codebase to resolve critical customer issues. Be able to systematize your learnings from customer engagements by creating reusable tools, building documentation and accelerators, and establishing best practices that can be used across the organization. Serve as a critical feedback loop to our core Product and Engineering teams. Synthesize firsthand insights from the field to influence product strategy and identify gaps. Act as a subject matter expert, providing technical guidance and best practices to customers on agent improvement, performance tuning, CI/CD pipelines, and production readiness.