Staff Software Engineer, BigQuery Agentic AI
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- Health, dental, vision, life, disability insurance
- Retirement Benefits: 401(k) with company match
- Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
- Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
- 3 years of experience building generative AI, agentic frameworks (e.g., LangChain, AutoGen), back-end system design.
- Experience with large-scale distributed systems and with one or more of the following: Java/Go/Python/TypeScript.
- Experience integrating generative AI tools or LLM interfaces into workflows.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 8 years of experience in software development and in AI/ML or data analytics.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- Experience with Large Language Models (LLM) for code (e.g., Gemini), modern cloud infrastructure, and industry-standard developer tool frameworks.
- Familiarity with datawarehouse, BigQuery, ML lifecycle.
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.
BigQuery is a serverless platform processing millions of queries a second. Our mission is to move beyond simple automation and into the era of agentic AI, creating autonomous solutions that partner with users to solve complex data challenges.
Google Cloud accelerates digital transformation for every organization, and BigQuery is at the heart of that mission. As a Software Engineer in the Analytics AI organization, you will build the intelligent foundation for future data processing. In this role, you will design AI solutions that act as multipliers. You will architect agents capable of reasoning over vast datasets, optimizing pipelines, and assisting across the entire data lifecycle. You will work at the intersection of distributed systems and generative AI to ensure BigQuery remains the leader in intelligent data warehousing.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design and develop next-generation agentic solutions that handle complex reasoning for data ingestion, feature extraction, and model training.
- Build scalable systems that integrate Large Language Models (LLMs) with BigQuery’s core engine to create autonomous experts for varied user personas.
- Iterate on agentic frameworks, contributing to sophisticated tool-use, multi-step orchestration, and rigorous evaluation (evals) to ensure reliability at petabyte scale.
- Build experiences that streamline work of data practitioners, be it data analysts, engineers, scientists or admins.
- Partner cross-functionally with Product, Data Scientists, and Designers to define the roadmap for AI-native data journeys. Mentor and guide junior engineers, fostering technical excellence in generative AI and distributed systems.
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