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.
We are seeking a Software Engineer to build and scale core components of our Agentic Ecosystem Platform. In this role, you will design, develop, and maintain robust infrastructure for agentic operations, focusing on delivering complex third-party integrations before expanding to support first-party systems.
You will play a crucial part in realizing the agentic paradigm shift by translating technical requirements into highly reliable, production-ready solutions that integrate seamlessly across major Google products (including AIM, Gemini, Geo, and Shopping). By owning critical platform features from end-to-end, you will directly enhance system scalability, collaborate closely with cross-functional product teams, and expand the platform's capabilities to support new, innovative applications.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
Responsibilities
- Contribute to the design and implementation of core infrastructure for Agentic Integrations (with a focus on MCP Servers).
- Build domain-specific features leveraging generalist models (AIM/Gemini). Collaborate directly with vertical teams to execute tool orchestration, writing the critical code needed to ensure reliable and consistent user experiences.
- Write, test, and deploy surface-agnostic code that operates seamlessly across AIM, Gemini, and Geo. Implement well-defined components of the MCP2Agency bridge, ensuring all deliverables strictly adhere to data governance and privacy policies (e.g., SIAN).
- Deliver high-quality code for priority partner integrations within a globally distributed team.
- Build and maintain robust features that extend the search experience framework while upholding high standards for code and search quality.
Qualifications
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 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.
- 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Experience building developer-facing platforms, software development kits, or third-party integration frameworks.
- Experience with Model Context Protocol (MCP).
- Familiarity with Large Language Model (LLM) orchestration, tool-use (function calling), and agentic workflows.
- Ability to execute evaluations while documenting successes and failures to identify areas for improvement.
- Ability to investigate horizontal solutions to mitigate recurring losses and apply various optimization techniques to refine model performance.
- Passion for rapid prototyping and "hill-climbing" to solve for the nuances of specialized vertical domains.