AI Solutions Architect in Victoria, British Columbia at Premier Cloud

About Premier Cloud

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.

About the role

AI Solutions Architect: Bridging Business Vision and Technical Execution

As the core technical advisor in this role, you will be responsible for transforming high-level business challenges and executive concepts into practical, production-ready AI solutions for enterprise customers.

Your daily focus will be on driving the translation of strategic business requirements into clear, actionable AI solution architectures and functional Minimum Viable Products (MVPs). This requires continuous, high-impact engagement with diverse stakeholders—from C-level executives defining strategy to engineering teams implementing the final solution—to ensure successful deployment.

• Deliver production-ready AI solutions that solve business challenges. Translate goals into clear solution architectures and working prototypes (MVPs), engaging with all levels, from engineers to C-level executives.
• Design and deploy full agentic workflows using modern frameworks (ADK, MCP, A2A, LangChain, LlamaIndex) and Vertex AI Agent Builder.
• Design and champion data infrastructure (vector databases, RAG pipelines, chunking) to prepare data for internal and customer use.
• Lead Discovery & Scoping and define objectives, metrics, and constraints with customer leadership. Rapidly scope solutions, moving from concept to proof-of-concept in weeks.
• Enable & Educate Advise stakeholders on AI capabilities and best practices through workshops and demos to drive adoption and build confidence in AI transformation.

Qualifications

• 4+ years designing and deploying AI/ML solutions, preferably in a customer-facing or consulting role.
• Hands-on experience building agentic workflows using modern frameworks (LangChain, LlamaIndex, ADK).
• Strong expertise in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face).
• Practical knowledge of LLM applications, RAG pipelines, vector embeddings, and prompt engineering.
• Working knowledge of Google Cloud Platform, including Vertex AI (Agent Builder, Model Garden), BigQuery, and Cloud Run.
• Outstanding presentation skills for both technical and executive audiences.
• Proven ability to translate complex AI concepts into actionable business strategies and forge relationships with customer leadership.
• Experience in preparing data, performing feature engineering, and making AI systems ready for production.

Core Competencies:

• Rapidly acquire new technical knowledge and demonstrate strong learning agility.
• Be a proactive problem-solver driven to find solutions.
• Ability to scope solutions, pivot quickly based on feedback, and architect solutions in real-time.

Preferred Qualifications:

• Google Cloud Professional Machine Learning Engineer or Data Engineer certification (or a commitment to achieve one within 6 months).
• Experience in sales calls and Statement of Work (SOW) creation.
• Familiarity with Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols.
• Experience with MLOps, containerization (Docker, Kubernetes), and CI/CD pipelines.
• Background in consulting or professional services.

Technical Environment

• Core AI Stack: Vertex AI Agent Builder, ADK, Gemini APIs, LangChain, LlamaIndex, MCP, A2A protocols.
• ML & Python, TensorFlow, PyTorch, Hugging Face, RAG pipelines, and vector databases.
• GCP Services: BigQuery, Dataflow, Cloud Run, GKE, Pub/Sub, Cloud Functions.
• Development: Docker, Kubernetes, GitHub Actions, Vertex AI Pipelines.

Expectations

• Daily interaction with customers (discovery, technical discussions, standups, executive presentations).
• Up to 30% travel to customer sites, Google offices, and industry events.
• Work closely with Cloud Architects, Google Cloud specialists, and internal teams on complex projects.