Gen AI Solutions Engineer #124
Summary
Build and deploy agentic AI systems on Google Cloud for enterprise customers, designing RAG pipelines, workflows, and production-ready MVPs while advising stakeholders.
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.
