info_outline XGoogle will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa. Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience with software programming in Python or C++. 1 year of experience in a core ML domain, including but not limited to generative AI, Natural Language Processing (NLP), computer vision, speech/audio, reinforcement learning, recommendation systems, or ML infrastructure. 1 year of experience with ML infrastructure (e.g., model training, model inference, model deployment, model evaluation, optimization, data processing, debugging). Preferred qualifications: Master's degree or PhD in Computer Science, or a related technical field. 2 years of experience with data structures and algorithms. Ability to quickly read and understand complex codebases. Ability to embrace ambiguity, and constantly level up debugging and system architecture skills. Strong core programming skills, with the ability to interact effectively and ethically with Large Language Models (LLMs) to drive productivity. Interest in agentic workflows, LLMs, developer productivity tools, and AI safety. About the job 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. With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions. As a key member of the Acceleration Platform team in Singapore, you will own the design and implementation of AI-native agentic systems that eliminate developer toil globally. In this role, you will lead zero-to-one technical initiatives, building scalable, resilient frameworks for self-sustaining AI at an enterprise scale. You will help set the bar for AI engineering excellence, mentoring junior peers and ensuring our distributed systems are secure-by-default and highly performant. The Core team builds the technical foundation behind Google’s flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google’s products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company. Responsibilities Design and build self-sustaining systems where AI agents reason, plan, and execute complex workflows to solve real-world engineering problems. Blend traditional software development with advanced prompt engineering, Retrieval-Augmented Generation (RAG), and optimization to build highly capable AI applications. Move beyond standard testing by creating evaluation pipelines to measure AI performance, mitigate, and ensure secure-by-default agent behavior. Troubleshoot non-deterministic AI behaviors. Investigate model introspection, refine system prompts, and optimize context to keep our self-sustaining systems on track. Accelerate productivity using AI coding assistants, and collaborate with global teams to discover groundbreaking new ways LLMs can eliminate developer toil.