About the role

Gen AI Solutions Engineer — Premier Cloud

Location: Victoria, BC, Canada Job Type: Full-time Travel: Up to 30% (customer sites, Google offices, industry events)

The Role

As a Gen AI Solutions Engineer, you'll turn enterprise AI ambitions into working software. You'll run technical discovery with customer teams, design agentic workflows on Google Cloud Vertex AI, and act as a trusted advisor to both engineers and executives — moving fast from whiteboard concept to a live, production-grade MVP.

What You'll Do

Design and build agentic systems

• 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

Prepare data for AI systems

• Design vector databases, RAG pipelines, and chunking strategies that make agents effective in production
• Curate and structure data so agents are ready for both internal and customer-facing use

Lead discovery and scoping

• Run discovery workshops with customer leadership to define objectives, constraints, and success metrics
• Scope and deliver MVPs in weeks, not months
• Present technical roadmaps that connect AI capabilities to business outcomes

Advise and enable customers

• Serve as the primary technical point of contact for enterprise accounts, from engineers to C-level stakeholders
• Run workshops and demos, and transfer knowledge so customers can sustain and extend what you've built
• Educate stakeholders honestly on AI capabilities and limitations, building the trust that drives adoption

What You Bring

Required

• 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

We especially encourage you to apply if: You're strong on learning agility and problem-solving even if your background doesn't check every box above. We'd rather hire for trajectory and curiosity than a perfect keyword match.

Technical Environment

• Core AI stack: Vertex AI Agent Builder, ADK, Gemini APIs, LangChain, LlamaIndex, MCP, A2A
• ML tooling: Python, TensorFlow, PyTorch, Hugging Face Transformers, RAG pipelines, vector databases
• GCP services: BigQuery, Dataflow, Cloud Run, GKE, Pub/Sub, Cloud Functions
• DevOps: Docker, Kubernetes, GitHub Actions, Vertex AI Pipeline

Team & Reporting

You'll work closely with Cloud Architects and Google Cloud specialists on complex customer implementations. (Add: who this role reports to, and team size, if you want to strengthen candidate confidence.)

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

Benefits

• Competitive Compensation: A package reflecting your technical expertise and sales-enabling impact.
• Growth & Development: Dedicated budget and time for continuous Google Cloud certifications and training.
• Collaboration with Google: High visibility and direct partnership with Google sales and engineering teams.
• Comprehensive Benefits: Full health coverage, paid time off, and relocation assistance (where applicable).
• Work Environment: Flexible remote work with top-tier equipment and an autonomous, trust-driven team culture.