Gen AI Solutions Engineer #124

About this position Premier Cloud is a Google Cloud Premier Partner dedicated to helping organizations modernize, collaborate, and scale through the power of cloud technology. Founded in 2001, we deliver cloud consulting, managed services, and tailored solutions to SMB and enterprise clients across North America.

As one of Canada’s fastest-growing companies, we help businesses unlock the full potential of Google Cloud, along with leading SaaS platforms like JumpCloud, Lumin, and Virtru. Our team is driven by innovation, technical excellence, and a shared commitment to delivering measurable impact for our clients.

At Premier Cloud, we take pride in maintaining a collaborative, light-hearted culture that values creativity, growth, and inclusion. Year after year, we’re recognized as a Great Place to Work-Certified™ organization and featured among the Best Workplaces in Technology.

Join as a Gen AI Solutions Engineer — Premier Cloud

Job Type:

Full-time

Travel:

Up to 30% (customer sites, Google offices, industry events)

Salary Range:

$125,000 – $200,000 CAD per year. Actual base salary is based on individual qualifications, experience, and expertise. Total compensation includes performance-based bonuses alongside a comprehensive benefits package.

As a Google Cloud Premier Partner, Premier Cloud helps SMB and Enterprise clients across North America modernize and innovate through cloud-native solutions, specialized consulting, and managed services.

Recognized as one of Canada’s fastest-growing companies with offices in Victoria, BC, and Austin, TX. Certified as a "Great Place to Work" for six consecutive years. Expertise spans Google Workspace migrations, AI/Data infrastructure, and strategic cloud consulting.

The Role & Core Responsibilities As a Gen AI Solutions Engineer, you will lead the architecture, design, and delivery of enterprise-scale Generative AI solutions on Google Cloud Platform. You will run technical discovery with customer teams, design agentic workflows on Vertex AI, and act as a trusted advisor to both engineers and executives — moving fast from whiteboard concepts to production‑grade MVPs. This role requires a strong combination of cloud architecture, MLOps, and hands‑on experience deploying scalable AI workloads.

Design and deploy agents using Agent Development Kit (ADK), Model Context Protocol (MCP), and Agent-to‑Agent (A2A) protocols. Build production systems with Vertex AI Agent Builder, LangChain, and LlamaIndex Architect end‑to‑end agentic workflows from concept through customer deployment Architect end‑to‑end multi‑agent systems and automated task assistants using Vertex AI Agent Builder, LangChain, or LlamaIndex. Build scalable Retrieval‑Augmented Generation (RAG) pipelines, configure semantic search, and integrate with vector databases. Lead client workshops to map out high‑impact, narrow use cases that show fast return on investment (ROI) Embed role‑based access, prompt safeguards, and data privacy controls directly into AI models from day one. Run discovery workshops with customer leadership to define objectives, constraints, and success metrics, delivering MVPs in weeks. Serve as the primary technical point of contact for enterprise accounts, educating stakeholders on AI capabilities and limitations to drive adoption.

Qualifications 4+ years designing and deploying AI/ML solutions, ideally in a customer‑facing or consulting role Hands‑on experience building agents and agentic workflows with modern frameworks (LangChain, LlamaIndex, ADK) Strong Python skills and experience with ML frameworks (TensorFlow, PyTorch, scikit‑learn, Hugging Face) Practical experience with LLM applications, RAG pipelines, vector embeddings, and prompt engineering Working knowledge of Google Cloud Platform, particularly Vertex AI (Agent Builder, Model Garden), BigQuery, and Cloud Run Strong presentation skills across technical and executive audiences Experience with data preparation and feature engineering for production AI systems A track record of translating AI capabilities into business strategy and building relationships with customer leadership

Preferred

Google Cloud Professional Machine Learning Engineer or Data Engineer certification (or willingness to earn one within 6 months) Experience supporting sales calls or writing statements of work Background in consulting or professional services with distributed/remote teams BigQuery, Dataflow, Cloud Run, GKE, Pub/Sub, Cloud Functions DevOps: Docker, Kubernetes, GitHub Actions, and Vertex AI Pipelines. Health, dental, and vision insurance Paid time off Ongoing training and certification support

Our Commitment to Inclusion Premier Cloud is an equal‑opportunity employer. We value diverse backgrounds and perspectives, and we encourage you to apply even if you don't meet every qualification listed

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