Senior Software Engineer, GenAI GCBP

Google • Sunnyvale, CA

17h

About The Position

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. Google Cloud Business Platforms (GCBP) is seeking an experienced Senior Engineer to be the driving force behind the intelligence and reliability of our AI agents. In this role, you will own the entire agent quality lifecycle, ensuring our agents can successfully reason, use tools, and execute complex tasks for our users. You will achieve this by designing and optimizing the critical prompts that guide them, building sophisticated evaluation frameworks, and leading the charge in testing for robustness and safety to create a truly trustworthy AI experience. 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. The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google [https://careers.google.com/benefits/].

Requirements

• 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.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Nice To Haves

• Experience in developing and deploying AI solutions for enterprise applications.
• Experience with Generative AI, Large Language Models (LLMs), Natural Language Processing (NLP), or agent-based systems.
• Deep understanding of AI/ML concepts, algorithms, and software architecture.
• Familiarity with cloud platforms (e.g. GCP) and MLOps practices.
• Strategic thinker with the ability to translate complex technical concepts into business value.

Responsibilities

• Be the driving force behind the intelligence and reliability of our AI agents.
• Ensure our agents can successfully reason, use tools, and execute complex tasks on behalf of our users.
• Take ownership of the entire agent quality lifecycle, from designing and optimizing the critical prompts that guide them to developing the sophisticated evaluation frameworks that measure their success.
• Lead the charge in testing our agentic systems for robustness, creating strategies to mitigate risks like prompt injection and tool-use failures.
• Build automated systems to continuously validate agent behavior, analyze interaction data, and generate key insights needed to make our agents smarter, faster, and more trustworthy.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level