AI Research Engineer - Code Search Platform

AI Research Engineer, Code Search

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• Experience in developing and deploying Generative AI agents.
• Experience with storage systems design, implementation, and management.
• Experience in natural language processing (NLP), image generation, or other generative AI techniques.

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
  
• Experience in text/code embeddings at scale, and with C++ programming language.
• Experience with infrastructure and building scalable distributed systems.
• Knowledge of GenAI, RAG, Agents.

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.

We work to create a seamless and intuitive exploration agent that accelerates development workflows and fosters knowledge sharing across Google.
In this role, you will be at the forefront of next generation code exploration, shaping the future of developer agents, improving the productivity and efficiency of developers and agents across Google, accelerating innovation and product development. You will collaborate with engineers, researchers, and designers across various teams and disciplines, contributing to a critical platform with opportunities for learning, growth, and career development. You will work on a platform that indexes and searches billions of lines of code, serving thousands of Google engineers daily.

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.

We work to create a seamless and intuitive exploration agent that accelerates development workflows and fosters knowledge sharing across Google.

Responsibilities

• Partner with agent teams (e.g., Gemini Coder, Duckie, Basecamp) to create sub-agents, tools, RAG solutions and workflows enabling them to do better code exploration.
• Integrate LLMs, RAG skills to augment code search with features like natural language code search, chat agents.
• Design, develop, and maintain core features of the Google code search platform, used by thousands of engineers daily.
• Improve the efficiency and scalability of code search infrastructure, ensuring fast response times and high availability.
• Analyze user data and conduct A/B testing to measure the effectiveness of new features and identify areas for improvement. 

Experience Level

Mid Level