Senior Test Automation Engineer - GCP Agentic AI
About The Position
The Senior Test Automation Engineer - GCP Agentic AI Engineer leads the architecture, development, and deployment of enterprise-scale Generative AI and Agentic AI solutions on Google Cloud Platform (GCP), leveraging Vertex AI and Gemini models. The role designs production-grade Retrieval-Augmented Generation (RAG) architectures, grounding strategies, embedding frameworks, and autonomous multi-agent systems to deliver accurate, scalable, business-driven AI outcomes. The position provides technical leadership through architecture reviews, proof-of-concepts, solution design, troubleshooting, and delivery governance. It also collaborates with cross-functional stakeholders and mentors engineering teams to advance AI innovation, best practices, and successful business outcomes. The role may be remote or based in Nashville, Tennessee.
Requirements
- Strong hands-on experience with GCP, particularly Vertex AI, for building and deploying enterprise-scale Generative AI solutions.
- Proven expertise designing and implementing RAG architectures, including document ingestion, retrieval pipelines, and contextual response generation.
- Deep understanding of embeddings, vector databases, semantic search, and grounding techniques.
- Extensive experience developing Agentic AI and multi-agent systems using frameworks such as LangChain and related orchestration technologies.
- Advanced Python programming skills and enterprise application development experience using Java, C#, or Node.js.
- Strong knowledge of SQL and NoSQL databases, including data modeling, optimization, and integration with AI-driven applications.
- Experience building cloud-native and containerized applications using Docker, Kubernetes, microservices, and serverless architectures.
- Background in DevOps, CI/CD, MLOps, and AI model lifecycle management.
- Technical leadership, stakeholder management, problem-solving, and communication skills, with a track record of leading teams and delivering AI transformation initiatives.
Responsibilities
- Lead the design, development, and deployment of enterprise-grade Generative AI and Agentic AI solutions on GCP using Vertex AI.
- Architect and implement scalable RAG solutions, including data ingestion, embeddings, vector search, and retrieval pipelines.
- Develop and optimize grounding and embedding strategies to improve response accuracy, relevance, and factual consistency.
- Build and manage Agentic AI and multi-agent systems for autonomous decision-making, orchestration, and task execution.
- Integrate LLMs with enterprise applications, APIs, and external tools using structured interaction frameworks such as Model Context Protocol (MCP).
- Design and deploy cloud-native AI applications using Docker, Kubernetes, microservices, serverless technologies, and modern MLOps/CI-CD practices.
- Provide technical leadership through architecture reviews, proof-of-concepts, solution design, troubleshooting, and delivery governance.
- Collaborate with cross-functional stakeholders and mentor engineering teams to drive AI innovation, best practices, and business outcomes.
Benefits
- Paid time off, including vacation, company-paid holidays, personal days, and sick leave, according to employee grade and policy.
- Medical coverage.
- Dental coverage.
- Vision coverage.
- Retirement savings plans, such as a 401(k) in the U.S. or RRSP in Canada.
- Life insurance.
- Disability insurance.
- Employee assistance programs.
- Additional benefits as provided by local policy and eligibility.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
