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Senior AI Solutions Engineer — Enterprise GCP

Syndesus, Inc.

North Vancouver · Hybrid Full-time Senior Today

About the role

About the Company

Our client is a Google Cloud partner operating at the intersection of enterprise AI and intelligent automation. They work directly with mid-to-large enterprises to design and deploy production-grade generative AI and agentic systems — helping organizations move beyond consumer-grade AI experimentation and into secure, governed, enterprise-ready solutions built on Google Cloud.

This is a nimble, high-agency environment. The team is small, the clients are real, and the problems are genuinely unsolved. You won't be maintaining someone else's roadmap — you'll be helping build one.

The Role

This is a founding technical role within the company's North American AI practice. You'll be the primary architect and solutions engineer driving customer engagements from initial conversation through to solution design and handoff to the delivery team. Think less "hands-down-in-the-IDE" and more forward-deployed technical expert — someone who can sit across from a CIO, understand their business problem, and translate it into a credible, production-ready AI solution on GCP.

You'll work closely with the founding leadership team and will have meaningful input into how the practice is built, which frameworks get adopted, and what the company's AI IP evolves into.

What You'll Be Doing

  • Leading technical discovery and solution design for enterprise AI engagements, primarily on Google Cloud (Vertex AI, Gemini Enterprise)
  • Architecting agentic AI systems that integrate with enterprise data sources — ERP systems, legacy platforms, modern data infrastructure — with full consideration for security, governance, data quality, and authorization frameworks
  • Translating complex business logic into scalable, production-grade AI solutions and communicating those designs clearly to both technical and business stakeholders
  • Collaborating with and directing offshore delivery teams to bring architectures to life
  • Contributing to and evolving the company's existing AI IP and accelerators
  • Staying sharp on the rapidly shifting agentic AI landscape — frameworks, tooling, and emerging best practices — and bringing that knowledge to bear for clients who are looking to you for guidance

What You Bring

  • Deep, hands-on experience with Google Cloud Platform — Vertex AI, Model Garden, Gemini — and a strong understanding of what enterprise GCP deployment actually looks like in practice
  • Proven experience building agentic AI systems — multi-step reasoning, tool use, state management, workflow orchestration — not just LLM prompting
  • Strong software engineering fundamentals — you understand that AI is maybe 20% of the solution; the rest is robust, scalable, maintainable engineering
  • Fluency across the enterprise AI considerations that actually matter in production: data governance, security, authentication/authorization, auditability, privacy
  • Experience working with or integrating enterprise data sources — ERP systems, legacy platforms, databases — and understanding how to make that data AI-ready
  • Excellent communication skills — you can hold a room with a CIO as comfortably as you can whiteboard an architecture with an engineering team
  • Comfortable with ambiguity, ownership, and operating without a large supporting cast

Nice to Have

  • Familiarity with other cloud platforms (AWS, Azure) — cloud literacy translates
  • Exposure to additional agentic frameworks (LangGraph, ADK, CrewAI) or other AI ecosystems (Anthropic, OpenAI)
  • Background in consulting, systems integration, or pre-sales solutions engineering

The Setup

  • Mostly remote with a downtown Toronto office available; occasional in-person team meetups (roughly monthly)
  • Compensation details to be confirmed — expect a package commensurate with the seniority and scope of this role
  • Full-time permanent position

Who Thrives Here

You've got enterprise pedigree — you've seen how large organizations actually work, what governance looks like at scale, and why "just build a chatbot" isn't a real answer. But you're not waiting for six approvals to make a decision. You move fast, you think broadly, and you're genuinely excited about being first in the door on problems that most companies are still figuring out how to frame.

Skills

AWSAzureDockerGCPGeminiLangGraphOpenAIVertex AI

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