Staff AI Solutions Deployment Developer – Google, Waterloo, ON
Location: Waterloo, ON | Company: Google
Google is hiring a Staff AI Solutions Deployment Developer in Waterloo, Ontario, to help strategic enterprise customers deploy production-ready agentic AI solutions through Google Cloud Applied AI.
This senior customer-facing technical position connects product development, software engineering and enterprise consulting. The successful candidate will help organizations turn complex business requirements into dependable AI systems that combine large language models, reasoning workflows, application programming interfaces and established enterprise platforms.
Deploying Enterprise AI Solutions
The Staff AI Solutions Deployment Developer will work within Google Cloud Applied AI, a group focused on helping organizations adopt Gemini Enterprise and other packaged AI solutions. The position goes beyond demonstrating technology. It involves helping customers design, test and implement systems that can operate reliably within real business environments.
The role sits between Google’s customers, product teams and developers. The successful candidate will examine business challenges, identify where agentic AI may provide value and help create the technical architecture required to move from an initial concept into a working production deployment.
Key Areas of Responsibility
The position combines software development, technical consulting, customer deployment and architectural leadership. Projects may involve several internal and external stakeholders, evolving AI capabilities and complex enterprise technology environments.
Agentic AI Architecture
Help define reasoning paths, API-connected tools and operational guardrails that allow autonomous AI agents to complete useful business tasks safely and consistently.
Customer Deployments
Support technical engagements from early design through implementation, helping strategic customers integrate AI solutions into their existing systems and workflows.
Technical Escalations
Investigate high-impact deployment issues and provide debugging, architectural guidance and practical recommendations to customer developers and senior stakeholders.
Pre-Release Testing
Deploy features before general availability in real customer environments to evaluate performance, identify limitations and provide useful feedback to product teams.
Enterprise Integration
Connect non-deterministic language-model outputs with structured business platforms such as SAP and Salesforce while maintaining appropriate controls and predictable system behaviour.
Deployment Best Practices
Help establish reusable technical methods, architectural frameworks and delivery practices that allow Google Cloud teams to implement AI solutions more efficiently.
Experience and Technical Qualifications
Google requires a bachelor’s degree in science, technology, engineering, mathematics or equivalent practical experience. Candidates should also bring at least eight years of experience in customer-facing technical roles such as solutions architecture, technical consulting or forward-deployed engineering, with a focus on enterprise systems.
The position also requires at least three years of programming experience using languages such as Python or Java. Applicants should understand large language models, prompt development and conversational AI frameworks. A master’s degree in engineering, computer science or a related technical discipline is listed as a preferred qualification rather than a mandatory requirement.
Skills That May Help Candidates Succeed
This position requires someone who can build software while also working directly with customers and senior business leaders. Strong candidates will be able to translate between technical possibilities, enterprise constraints and measurable business needs.
Experience designing scalable AI systems helps candidates connect language models, data sources, APIs and existing enterprise applications.
The ability to understand customer requirements and explain technical decisions clearly is important throughout complex, multi-stage deployments.
Strong software development practices help ensure that prototypes can become secure, maintainable and dependable production services.
Candidates should be comfortable guiding cross-functional teams, influencing executive stakeholders and creating direction when requirements are still developing.
Understanding how AI components interact with governance, security, procurement and established business platforms supports safer enterprise adoption.
Compensation and Preferred Work Location
The Canadian location listed for this position is Waterloo, Ontario. Applicants may also have the opportunity to indicate Cambridge, Massachusetts, or New York City as a preferred work location during the application process. The role requires English proficiency to support communication and collaboration across Google’s global teams and customer organizations.
For the Canadian position, Google lists a base salary range of CAD $204,000 to $210,000, along with a 20% target bonus, discretionary equity and benefits. Individual compensation is determined using factors such as relevant skills, professional experience, education and training. Equity awards remain subject to company approval, applicable plans and individual grant agreements.
How to Apply
Candidates should review the full vacancy on Google’s official careers website before applying. The official posting contains current information about qualifications, responsibilities, compensation, workplace locations, privacy terms and accommodation support during the recruitment process.
Applicants should prepare a résumé that clearly describes customer-facing technical experience, enterprise architecture work, programming ability and deployments involving large language models or conversational AI. Relevant experience with Google Cloud, SAP, Salesforce, telecommunications, security governance or complex production systems should also be highlighted where applicable.