Forward Deployed Developer III, Generative AI – Google – Toronto, ON
Location: Toronto, ON | Company: Google
Google Cloud is looking for a Forward Deployed Developer III, Generative AI to join its Go-To-Market team in Toronto, ON or Montreal, QC. This is a hands-on builder role at the frontier of enterprise AI — not an advisory position, but a deeply technical one where you’ll embed with strategic customers and ship production-grade agentic systems directly in their environments.
If you have a founder’s mindset and thrive on turning cutting-edge AI capabilities into real-world business outcomes, this role puts you at the centre of Google’s AI revolution. You’ll work with Gemini models, the Vertex AI platform, and have direct access to DeepMind’s engineering and research expertise.
About the Role: Forward Deployed Developer III, Generative AI
As a GenAI Forward Deployed Developer, you’ll act as an embedded builder who bridges the gap between Google’s frontier AI products and production-grade deployment within customer environments. You’ll move beyond high-level architecture to actively code, debug, and co-ship bespoke agentic solutions — solving integration complexities, data readiness issues, and state-management challenges that stand between AI prototypes and enterprise-grade maturity.
Working alongside technical sales teams and customer stakeholders, you’ll also serve as a critical feedback loop — translating real-world field insights directly into Google Cloud’s future product roadmap. Your work will span multi-agent systems, observability frameworks, and building the connective tissue between Google’s AI stack and customer infrastructure.
Benefits and Salary
The base salary range for this full-time position in Canada is CAD $150,000–$154,000, plus bonus, equity, and a comprehensive benefits package. Salary is determined by role, level, and location, with individual pay also factoring in experience, skills, and relevant education. For full details on what Google offers, visit their benefits page directly.
Job Details
📌 Job Type: Full-Time
🏢 Company: Google
📍 Location: Toronto, ON or Montreal, QC, Canada
💰 Pay: CAD $150,000–$154,000 base salary + bonus + equity + benefits
Responsibilities
This role sits at the intersection of software engineering and enterprise AI deployment. You’ll be responsible for taking AI-driven solutions from prototype to production within customer environments, while also contributing to Google Cloud’s product direction through field insights. Here’s what the work looks like day to day:
- Develop and deploy complex AI applications, transitioning from rapid prototypes to production-grade agentic workflows (e.g., multi-agent systems, Model Context Protocol servers) that drive measurable ROI for customers
- Architect and code the integration layer between Google’s AI products and customers’ live infrastructure, including APIs, legacy data silos, and security perimeters
- Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet rigorous standards for accuracy, safety, and latency
- Identify repeatable patterns and friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for engineering teams
- Partner with technical sales teams to instil Google-grade development best practices, supporting long-term project success and high end-user adoption
Requirements / Skills
Google is looking for a high-agency developer who combines deep technical expertise in AI systems with the drive to deliver results in complex, customer-facing environments. The ideal candidate is comfortable working at the frontier of generative AI and can navigate both the technical and strategic dimensions of enterprise deployments.
- Bachelor’s degree in Engineering, Computer Science, or a related field — or equivalent practical experience
- 2+ years of software development experience using Python or similar coding languages
- Experience launching production-grade AI solutions end-to-end, including architecting AI systems on cloud platforms such as Google Cloud Platform (GCP)
- Experience building data pipelines for structured and unstructured data using vector databases and RAG-like architectures for enterprise AI solutions
- Preferred: Master’s or PhD in AI, Computer Science, or a related technical field
- Preferred: Experience implementing multi-agent systems using frameworks like LangGraph, CrewAI, or ADK, and complex patterns such as ReAct, self-reflection, or hierarchical delegation
- Preferred: Knowledge of LLM-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing
How to Apply
To apply for this Forward Deployed Developer III, Generative AI position at Google Cloud, click the link below to visit the official job posting. Make sure your resume is current and reflects relevant experience with AI systems, cloud platforms, and production-grade development.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Forward Deployed Developer III, Generative AI role at Google Cloud in Toronto (or Montreal) is ideal for candidates who excel in production-grade AI development, agentic system architecture, and cloud platform engineering. On your resume, emphasize hands-on experience with Python, RAG architectures, vector databases, and end-to-end AI solution delivery on platforms like GCP. If you’ve worked in enterprise AI deployments, customer-facing technical roles, or built multi-agent systems, make sure to highlight the specific outcomes and production systems you’ve shipped.
Resume & Application Tips: Before applying, tailor your resume to match the job description. Include keywords like generative AI, agentic workflows, Vertex AI, multi-agent systems, and LangGraph that appear in the posting. Quantify your achievements where possible (e.g., “reduced AI pipeline latency by 40%” or “deployed RAG architecture serving 10,000+ enterprise users”). A brief cover letter expressing your interest in Google Cloud’s AI mission and your experience with production AI systems will strengthen your application. Double-check your application for errors and ensure your contact information is current.
Interview Preparation: If selected for an interview, research Google Cloud‘s AI product portfolio, Gemini models, and the Vertex AI platform beforehand. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your experience with AI system architecture, customer collaboration, and production deployment challenges. Common questions may include technical deep-dives on multi-agent patterns, RAG implementation, and scenarios involving cross-functional collaboration with enterprise clients. Dress professionally, arrive 10–15 minutes early (or log in early for virtual interviews), and bring copies of your resume. Prepare thoughtful questions about the team’s current projects, Google Cloud’s product roadmap, and how field insights influence engineering priorities. After the interview, send a thank-you note within 24 hours reiterating your enthusiasm for the role.