
Organizing the world's information and making it universally accessible.
Staff Software Engineer, Generative AI, Applied AI, Research
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.
With your technical expertise you will manage project priorities, deadlines, and deliverables. You will design, develop, test, deploy, maintain, and enhance software solutions.
Our agile Artificial Intelligence (AI) team seeks a highly motivated AI Research Engineer passionate about managing issues and delivering innovative solutions at breakneck speed. We develop agentic AI solutions for impactful enterprise use cases. In this role, you will be inventing, designing, and deploying systems, focusing on algorithmic innovations for sophisticated agentic AI. This includes improving performance on high-priority directions like multi-agent systems, reinforcement learning, multimodal reasoning, data-centric approaches, evaluation innovations, and enhancing Large Language Model reliability and tool use for enterprises. Your work will directly influence the next wave of AI innovation, turning research into practical, high-impact solutions that solve critical real-world issues.
Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google Deep Mind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.
For United States Applicants:
The US base salary range for this full-time position is $207,000-$300,000 + 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.
For Canada Applicants:
The Canada base salary range for this full-time position is CAD 216,000-221,000 + 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.
Please note that the compensation details listed in Canada role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
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Drive the technical strategy, architecture, and execution for ambiguous projects on our conversational AI platform. Define the technical roadmap for scalable, long-term solutions.
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Act as the lead engineering partner for product management and User Experience. Define product strategy, refine ambiguous customer needs into concrete technical designs, and drive consensus across teams.
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Manage and iterate on new platform capabilities to meet immediate customer needs.
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Balance this speed with long-term technical health, advocating best practices to ensure solutions are clean, maintainable, scalable, testable, and easy to refactor.
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Leverage user empathy to guide product direction, respond thoughtfully to customer feedback, and build intuitive, powerful, and seamless experiences for the developers who rely on our platform.
Minimum qualifications
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Bachelor’s degree or equivalent practical experience.
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8 years of experience in software development with C++.
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7 years of experience leading technical project strategy, ML design, and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications
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Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
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8 years of experience with data structures and algorithms.
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3 years of experience in a technical leadership role leading project teams and setting technical direction.
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3 years of experience working in an organization involving cross-functional, or cross-business projects.
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About Google

Google specializes in internet-related services and products, including search, advertising, and software.
10,001+
Employees
Mountain View
Headquarters
$1,700B
Valuation
Reviews
10 reviews
4.5
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Work-life balance
3.2
Compensation
4.3
Culture
4.1
Career
4.2
Management
3.8
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Pros
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Innovative and interesting work
Career development and learning opportunities
Cons
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Fast-paced and overwhelming environment
Salary Ranges
57,503 data points
Mid/L4
Mid/L4 · Accessibility Analyst
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$214,500
total per year
Base
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Bonus
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$214,500
$214,500
Interview experience
9 interviews
Difficulty
3.4
/ 5
Duration
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Offer rate
44%
Experience
Positive 0%
Neutral 56%
Negative 44%
Interview process
1
Application Review
2
Online Assessment/Technical Screen
3
Phone Screen
4
Onsite/Virtual Interviews
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Team Matching
6
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