Gen AI Solutions Engineer #124
Premier Cloud Victoria, Prince Edward Island, Canada · CA$125K–CA$200K/yr
IT Services and IT Consulting · 11-50 employees
About the role
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.
What they look for
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.
Benefits
Full description
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
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