Software Engineer, Content Safety, AI Transformation Enablement

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 unblocks and accelerates 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

• Build high-quality systems that help your team deliver on its commitments to clients, ensuring effective and performant solutions to content safety problems.
• Own the design and implementation of robust, modular software components to ensure clean, readable, and maintainable code.
• Implement and maintain both stateless and stateful agentic flows, supporting multi-step AI orchestration pipelines that interact securely with Application Programming Interfaces (APIs), databases, and external tools.
• Develop and test validation gates, routing logic, and tool-use schemas to guarantee deterministic and compliant execution within our autonomous safety agent pipelines.
• Build and deploy production-grade content safety solutions across both server-side and on-device environments.

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), or specialization in another ML field.

Preferred qualifications:

• Experience integrating Generative AI APIs, foundation model Software Development Kits (SDKs), and calling cloud-hosted models within software applications.
• Experience designing clean software components, modular interfaces, and robust data models within complex systems.
• Experience implementing or testing agentic flows (e.g., both stateless and stateful) and multi-step AI orchestration pipelines, including prompt engineering and tool-use (e.g., function calling) schemas.
• Basic understanding of ML concepts and how Large Language Models (LLMs) work (e.g., high-level mechanics of transformers, embeddings, or model activations).
• Familiarity with or interest in Responsible AI or safety-adjacent fields such as factuality, policy enforcement, or adversarial defense.