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 Agent Optimization and Augmentation team is building the operational support for Gemini Enterprise for Customer Experience. Our goal is to provide best customer interfaces with embedded multimodal intelligence, creating full-stack concierges capable of complex reasoning and seamless sales orchestration.
We are focused on the meta-layer of AI, creating a suite of agents designed to build, test, and improve other agents. By leveraging Google’s foundational AI (Gemini and Vertex AI), we are transforming agent development from a manual, iterative process into a precise and optimized engineering artifact.
Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Build the core logic for multimodal full-stack concierge agents that execute complex reasoning across sales and support.
- Develop automated systems and tools that allow agents to iteratively build, test, and refine other agents.
- Architect the pathways that embed Gemini and Vertex AI intelligence directly into client-facing Cloud infrastructure.
- Establish engineering benchmarks to replace manual trial-and-error testing with automated, high-fidelity optimization.
- Partner with Cloud clients to identify bottlenecks and deploy rapidly customizable agent solutions.
Qualifications
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years 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.
- 5 years of experience testing, and launching software products.
- 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 3 years of experience with software design and architecture.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- Experience launching and maintaining high-availability consumer-facing AI products.
- Ability to work in a fluid, 0-to-1 environment with evolving requirements.