Gen AI Solutions Engineer #122

Premier Cloud • Austin, TX

10d • Hybrid

About The Position

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.

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.

Requirements

• 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

Nice To Haves

• 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.

Responsibilities

• 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.

Benefits

• Health, dental, and vision insurance
• Paid time off
• Ongoing training and certification support

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed