Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 1 year of experience with data structures and algorithms.
- 1 year of experience implementing core Machine Learning (ML) concepts.
- Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
Preferred qualifications:
- Academic, internship, or personal project experience integrating generative AI APIs and foundation model endpoints into software applications.
- Familiarity with building agentic workflows, including chaining model prompts, configuring model tool-use (e.g., function calling), and integrating foundation models with external APIs or databases.
- Basic familiarity with or a keen interest in learning about machine learning, natural language processing (NLP), or LLMs.
- Interest or coursework in Responsible AI, data privacy, product policy, or adjacent safety fields.
- Strong communication skills, a proactive attitude toward learning, and eagerness to collaborate in a global, multi-regional team environment.
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.
The Content Safety organization in Core provides safety solutions that protect Google’s users from exposure to offensive, sensitive or harmful content. The team unblock and accelerate Google's product launches by providing quality implementations of company-wide standards for Responsible Artificial Intelligence (AI). The team combines subject matter expertise in the content safety domain and a practice of machine learning and AI-based techniques with the production-grade experience in serving infrastructure and product integrations to protect users from harm, maintain Google’s engagement in the area of online safety across the industry, and make foundational models and the internet safer for society.
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
- Write and maintain high-quality, readable, and well-tested code for on-device and server-side content safety applications.
- Develop and test validation gates, routing logic, and tool-use schemas to ensure deterministic and compliant execution within our autonomous safety agent pipelines.
- Contribute to implementing and maintaining both stateless and stateful agentic flows, supporting multi-step AI orchestration pipelines that interact with Application Programming Interfaces (APIs), databases, and external tools to automate safety decisions.
- Support the team in delivering on commitments to clients, ensuring robust and performant solutions to user protection challenges.
- Collaborate closely with mentors and executive engineers to learn Google’s development processes, design patterns, and system architectures.