Senior Test Automation Engineer – GCP

This is a fully remote position, open to applicants in Tennessee.

📋 Description

• Take charge of the design, development, and deployment of enterprise-level Generative AI and Agentic AI solutions on the Google Cloud Platform utilizing Vertex AI.

• Create and implement scalable Retrieval-Augmented Generation (RAG) solutions, covering data ingestion, embeddings, vector search, and retrieval pipelines.

• Enhance grounding and embedding strategies to boost AI response accuracy, relevance, and factual consistency.

• Construct and oversee Agentic AI and multi-agent systems capable of autonomous decision-making, orchestration, and task execution.

• Integrate Large Language Models (LLMs) with enterprise applications, APIs, and external tools through structured interaction frameworks like the Model Context Protocol (MCP).

• Design and deploy cloud-native AI applications by leveraging Docker, Kubernetes, microservices, serverless technologies, and contemporary MLOps/CI-CD practices.

• Offer technical leadership via architecture reviews, proof-of-concepts (PoCs), solution design, troubleshooting, and delivery governance.

• Collaborate with cross-functional stakeholders and mentor engineering teams to foster AI innovation, best practices, and successful business results.

⛳️ Requirements

• Extensive hands-on experience with Google Cloud Platform (GCP), especially Vertex AI, for constructing and deploying enterprise-level Generative AI solutions.

• Demonstrated expertise in designing and implementing Retrieval-Augmented Generation (RAG) architectures, including document ingestion, retrieval pipelines, and contextual response generation.

• Profound understanding of embeddings, vector databases, semantic search, and grounding techniques.

• Significant experience in developing Agentic AI and multi-agent systems using modern frameworks like LangChain and associated orchestration technologies.

• Advanced programming capabilities in Python, along with experience in enterprise application development using Java, C#, or Node.js.

• Strong proficiency in SQL and NoSQL databases, covering data modeling, optimization, and integration with AI-driven applications.

• Experience in building cloud-native and containerized applications utilizing Docker, Kubernetes, microservices, and serverless architectures.

• Solid foundation in DevOps, CI/CD, MLOps, and AI model lifecycle management.

• Exceptional technical leadership, stakeholder management, problem-solving, and communication abilities, with a proven history of leading teams and executing successful AI transformation initiatives.

🏝️ Benefits

• Vacation: 12-25 days, based on grade.

• Company-paid holidays.

• Personal Days.

• Sick Leave.

• Medical, dental, and vision coverage.

• Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada).

• Life and disability insurance.

• Employee assistance programs.

• Other benefits as provided by local policies and eligibility.

• Variable incentives, bonuses, or commissions may be available depending on the position and applicable laws.