Artificial Intelligence Engineering Lead

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience in software development.
• 5 years of experience in testing and launching software products.
• 3 years of experience with software design and architecture.

Preferred qualifications:

• 10 years of experience in software development.
• 1 year of experience in building with Generative AI models.
• Experience in designing, building, and scaling RESTful APIs and back-end services on cloud platforms (e.g., Google Cloud).
• Experience with modern AI-assisted coding tools (e.g., Gemini CLI, Claude Code), and with emerging agentic AI frameworks and protocols (e.g., Google ADK, MCP, LangChain).
• Ability to prototype and iterate, translating ideas from concept to a functional prototype.

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.

In this role, you will be the expert on the latest Artificial Intelligence (AI) models and standards, ensuring the teams have access to technology. You will have experience with leading the teams, showcasing how to build workflows with foundation models, fine-tuned models, context engineering, memory systems, etc.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

Responsibilities

• Design, develop, and maintain a library of Application programming interfaces (APIs) and latest AI models from Google DeepMind and the ecosystem. Build workflows through context engineering, Retrieval-augmented generation (RAG), fine-tuning layers, etc.
• Serve as the AI engineering lead for the pods. Provide the AI techniques, back-end code, and infrastructure that turn concepts into functional prototypes within days.
• Own the operational backbone of the prototyping work. Manage the Google Cloud capacity, set up Continuous Integration/Continuous Deployment (CI/CD) systems, and architecting data repositories and APIs for the experiments.
• Advocate for engineering practices in a changing coding environment. Ensure the back-end systems are reliable and well-documented.
• Stay at the forefront of AI research and development. Be responsible for evaluating and integrating emerging models, tools, and standards (e.g., Google's Agent Developer Kit (ADK), Model Communication Protocol (MCP)).