Software Engineer, BigQuery Agentic AI
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
- 2 years of software development experience with a focus on AI/ML or Data Analytics.
- 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- Experience with one or more of Java/Go/Python/TypeScript.
- Experience in Generative AI, Agentic Frameworks (e.g., LangChain, AutoGen), Backend System Design, ML concepts and Cloud services (Google Cloud Platform, Cloud Computing Platform).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical fields.
- Experience building developer-facing products for integrated development environments (IDEs like VSCode) or Command Line (CLI).
- Experience with Large Language Models for code (e.g., Gemini, GPT-4, Claude), modern cloud infrastructure, and industry-standard developer tool frameworks.
- Familiarity with data warehousing concepts and BigQuery.
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.
As a Software Engineer in BigQuery’s Analytics AI organization, you will build the intelligent backbone for the next generation of data processing. Our mission is to move beyond simple automation and into the era of Agentic AI, creating sophisticated, autonomous solutions that partner with users to solve their most complex data challenges.
You will design and implement AI-native solutions that act as a multiplier and architect agents capable of reasoning over vast datasets, optimizing pipelines, and assisting across the entire data life-cycle, from ingestion and feature extraction to model training and advanced analytics. You will work at the intersection of large-scale distributed systems and Generative AI, partnering closely with product managers, engineers, data scientists, and designers to ensure BigQuery remains the industry leader in intelligent data warehousing.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $147000 - $211000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities:
- Lead the design and development of next-generation agentic solutions that handle complex reasoning for various data developer experiences such as data ingestion, data pipelines, data science, feature extraction, model training and more.
- Redefine the customer experience for Data Analytics with an AI-first focus.
- Architect systems that integrate Large Language Models (LLMs) with BigQuery’s core engine to create autonomous "experts" for user personas.
- Iterate on agentic frameworks, contributing to sophisticated tool-use, memory, context retrieval, multi-step orchestration, and rigorous evaluation (evals) to ensure accuracy and reliability of orchestration at petabyte scale.
- Partner cross-functionally with Product, Data Scientists, Applied Scientists, and UX Designers to define the roadmap for AI-native data journeys.