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.

Our team is leading the way in bringing Google's Applied AI to the market! Our mission is to pioneer the development of conversational AI, enabling developers to build generative AI agents capable of engaging in complex, open-ended dialogues and completing autonomous tasks. Core Infra provides the foundation for this mission driving critical efforts like Centralized Compliance, Conversation History Logging powering various customer facing and internal analytics.

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.

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

• Drive the technical direction and multi-year road map for conversational agent data systems, collaborating with Principal Engineers to align infrastructure capabilities with the evolution of Generative AI.

• Implement scalable, high-performance data solutions using Spanner and Google Cloud Platform (GCP), balancing the demands of real-time runtime storage with the complexity of massive-scale offline analytics.

• Act as the primary technical liaison for cross-functional partner teams, clarifying project scope and setting the direction for both the producers and consumers of core product data.

• Advocate a culture of production excellence by leading high-stakes design and code reviews across cross-site organizations.

• Lead critical infrastructure investments that address scalability bottlenecks, technical debt, and operations, guiding the team through complex migrations in a high-velocity environment.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development.

• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.

• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.

• 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

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.

• 3 years of experience in a technical leadership role leading project teams and setting technical direction.

• 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.