Staff Software Engineer, Google Health

Design and implement a unified, flat agentic architecture driven by tools and skills, streamlining both proactive wake-ups and reactive user interactions within a single conversational model.Lead engineering execution using spec-driven development with AI to ensure code, rules, and design are always in sync.Build and scale comprehensive evaluation and simulation frameworks to test multi-turn conversations and longitudinal user interactions using synthetic data and simulated user actors.Collaborate closely with Product Managers, UX Designers, and frontend engineers to establish server-driven generative UX. You will leverage cross-platform frameworks to enable agents to generate high-performance native UI components and dynamic features on the fly.Minimum qualifications:Bachelor’s degree or equivalent practical experience.8 years of experience in software development.5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.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 with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).Experience with Generative AI.Preferred qualifications:Master’s degree or PhD in Engineering, Computer Science, or a related technical field.8 years of experience with data structures and algorithms.3 years of experience in a technical leadership role leading project teams and setting technical direction.3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.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.Google for Health is a company-wide effort to help billions of people be healthier. We work toward this vision by meeting people in their everyday moments and empowering them to stay healthy and partnering with care teams to provide more accurate and accessible care. Our teams are applying our expertise and technology to improve health outcomes globally – with high-quality information and tools to help people manage their health and wellbeing, solutions to transform care delivery, research to catalyze the use of artificial intelligence for the screening and diagnosis of disease, and data and insights to the public health community.Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefitsLearn more about benefits at Google.Bachelor’s degree or equivalent practical experience.8 years of experience in software development.5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.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 with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).Experience with Generative AI.