Premier CloudVerified Job Source

Gen AI Solutions Engineer #124

Victoria, BC
Hybrid
Posted Aug 5, 2026
1 position

$125,000–$200,000 / year

Opens an external site

Employment type: Full-time
Experience level: Mid-level · 4+ years
Minimum education: Professional degree
Posting language: English
Working hours: 40 hours per week

Job summary

You will lead the architecture, design, and delivery of enterprise-scale Generative AI solutions on Google Cloud Platform. This involves running technical discovery workshops, designing agentic workflows, and serving as a trusted advisor to stakeholders.

Job details

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. About Premier Cloud 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 MLOps experience: Docker, Kubernetes, CI/CD pipelines Background in consulting or professional services with distributed/remote teams Vertex AI Agent Builder, ADK, Gemini APIs, LangChain, LlamaIndex, MCP, A2A ML tooling: Python, TensorFlow, PyTorch, Hugging Face Transformers, RAG pipelines, vector databases BigQuery, Dataflow, Cloud Run, GKE, Pub/Sub, Cloud Functions DevOps: Docker, Kubernetes, GitHub Actions, and Vertex AI Pipelines. Compensation & Benefits 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

What you’ll do

Requirements

Candidates must have 4+ years of experience designing and deploying AI/ML solutions with strong proficiency in Python and modern AI frameworks. Practical experience with LLM applications, RAG pipelines, and Google Cloud Platform is essential.