Gen AI Solutions Engineer #122
Premier Cloud · Austin, Texas, United States
IT Services and IT Consulting · 11-50 employees
About the role
You will design and build agentic AI systems using Google Cloud Vertex AI and modern frameworks to solve complex enterprise challenges. Additionally, you will lead technical discovery workshops and act as a trusted advisor to help customers deploy production-grade AI solutions.
What they look for
Requirements
Candidates must have 4+ years of experience in AI/ML solution design and hands-on proficiency with Python and agentic frameworks like LangChain or LlamaIndex. Strong communication skills are required to bridge the gap between technical implementation and business strategy for executive stakeholders.
Benefits
Full description
About the role
Gen AI Solutions Engineer — Premier Cloud
Location: Hybrid remote, Austin, TX 78701 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 Pipelines
Compensation & Benefits
- Health, dental, and vision insurance
- Paid time off
- Ongoing training and certification support
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
