AI Outcome Customer Developer, Forward Deployed Development – Google – Toronto, ON
Location: Toronto, ON | Company: Google
Google Cloud’s Go-To-Market AI Tech organization is hiring an AI Outcome Customer Developer, Forward Deployed Development based in Toronto, Ontario. This is a senior technical role sitting at the intersection of enterprise architecture, pre-sales technical evaluation, and post-sales delivery — a rare combination that puts you at the centre of Google’s AI revolution for businesses worldwide.
Working alongside account teams and Customer Developers during technical evaluation phases, you’ll shape how enterprise-grade AI solutions — including frontier Gemini models and the complete Vertex AI platform — actually integrate into complex customer IT ecosystems. From connectors and identity providers to data residency and legal compliance constraints, your fingerprints will be on the technical reality of delivery.
About the Role: AI Outcome Customer Developer
As an AI Outcome Customer Developer aligned with Google’s Forward Deployed Development (FDD) organization, you act simultaneously as an enterprise architect, technical debugger, development liaison, and delivery manager. You enter the agreement cycle during the technical evaluation phase for strategic AI accounts, ensuring solutions are shaped through the lens of adoption, rapid activation, and viable delivery. You bridge the gap between pre-sales agreement shaping and post-sales execution — a critical function for Google Cloud’s most strategic customers.
This role demands genuine depth: you’ll dive into code-level context to diagnose complex implementation issues, serve as the definitive liaison to core Product and Engineering teams, and translate real-world field feedback into actionable feature requests. You’ll also need to communicate seamlessly with executive stakeholders, translating deep technical integration challenges into clear business impact narratives.
Benefits and Salary
This position offers a base salary range of $198,000 – $202,000 CAD per year, plus a 20% bonus target, equity, and a comprehensive benefits package. For full details on Google’s benefits programme, visit Google’s careers benefits page.
Job Details
🏢 Company: Google
📍 Location: Toronto, ON, Canada
💰 Pay: $198,000 – $202,000 CAD/year + 20% bonus target + equity + benefits
Responsibilities
This role spans the full technical lifecycle of Google Cloud’s most strategic AI engagements. Day to day, you’ll be equally at home reviewing architecture diagrams, debugging integration code, and presenting to C-suite executives. The breadth of ownership here is significant — and intentional.
- Partner with account teams and practice Customer Developers during technical evaluation phases to assess project feasibility, shape proposals for long-term adoption, and validate FDD engagement requests
- Lead upfront technical design for enterprise-grade AI solutions, ensuring seamless and secure integration of models, agents, and connectors into existing customer data pipelines, identity providers, and compliance boundaries
- Diagnose and resolve complex customer implementation issues at the code level, identify core product bugs, and test workarounds to clear execution roadblocks
- Serve as the definitive liaison to core Product and Engineering teams, troubleshooting systemic deployment blockers and translating real-world field feedback into actionable feature requests
- Steer implementation strategy through technical authority and architectural foresight while owning the technical reality of delivery alongside customer-facing teams
Requirements / Skills
Google is looking for a deeply technical professional who can operate credibly at both the architectural and code levels, while also influencing executive stakeholders and shaping enterprise strategy. Strong communication skills are just as important as technical depth in this role.
- Bachelor’s degree or equivalent practical experience
- 7 years of experience with cloud native architecture in a customer-facing or support role
- Technical delivery strategy experience with interfacing with product or development organisations
- System design or code proficiency in languages such as Java, C++, or Python
- Orchestration framework experience with tools such as LangGraph, AutoGen, or CrewAI
- Enterprise integration experience covering APIs, enterprise content management (ECMs), identity, Cloud infrastructure, or AI/ML model deployments
- Executive communication skills capable of translating deep technical integration issues into business impact (preferred)
- Experience orchestrating specialised technical resources to execute complex builds (preferred)
How to Apply
To apply, visit the official Google Careers job posting using the link below. Make sure your resume is up to date and tailored to the technical and communication requirements of this role before submitting.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This AI Outcome Customer Developer role at Google in Toronto is perfect for candidates who excel in enterprise AI architecture, cloud native solution design, and technical stakeholder engagement. On your resume, emphasise any experience with AI/ML deployments, orchestration frameworks, and enterprise integrations, attention to detail, and your ability to work in a fast-paced, high-stakes environment. If you’ve previously worked in cloud solutions engineering, forward deployed engineering, or enterprise technical consulting, make sure to highlight specific achievements and responsibilities that align with this position.
Resume & Application Tips: Before applying, tailor your resume to match the job description. Include keywords like cloud native architecture, LangGraph / AutoGen / CrewAI, and enterprise AI integration that appear in the posting. Quantify your achievements where possible (e.g., “led technical evaluation for 10+ enterprise AI deployments” or “reduced integration blockers by 40% through proactive architectural review”). Write a brief cover letter expressing your genuine interest in Google Cloud‘s GTM AI mission and why you’re well positioned to contribute in Toronto. Double-check your application for spelling errors and ensure your contact information is current.
Interview Preparation: If selected for an interview, research Google Cloud‘s AI product portfolio — particularly Gemini models and Vertex AI — as well as Google’s recent announcements and company culture beforehand. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your architectural decision-making, debugging under ambiguity, and executive communication. Common questions may include scenarios about diagnosing complex integration failures, influencing product roadmaps based on field feedback, and managing technical delivery across cross-functional teams. Dress appropriately for a technology and enterprise software environment, arrive 10–15 minutes early (or log on early for virtual interviews), and bring copies of your resume. Prepare thoughtful questions about the FDD organisation, team structure, and growth pathways. After the interview, send a thank-you email within 24 hours reiterating your interest in the position.
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