Senior Test Automation Engineer – GCP

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

📋 Description

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

• Architect and execute scalable Retrieval-Augmented Generation (RAG) solutions, encompassing data ingestion, embeddings, vector search, and retrieval pipelines.

• Create and refine grounding and embedding strategies to enhance the accuracy, relevance, and factual consistency of AI responses.

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

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

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

• Provide technical leadership via architecture reviews, proof-of-concepts, solution design, troubleshooting, and oversight of delivery governance.

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

⛳️ Requirements

• Strong practical experience with Google Cloud Platform (GCP), especially Vertex AI, for the construction and deployment of enterprise-scale Generative AI solutions.

• Demonstrable 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.

• Extensive experience in developing Agentic AI and multi-agent systems using modern frameworks such as LangChain and related orchestration technologies.

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

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

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

• Solid expertise in DevOps, CI/CD, MLOps, and the management of AI model lifecycles.

• Exceptional technical leadership, stakeholder management, problem-solving, and communication abilities.

• Proven history of leading teams and successfully delivering AI transformation initiatives.

🏝️ Benefits

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

• Company paid holidays.

• Personal Days.

• Sick Leave.

• Medical, dental, and vision coverage (or provincial healthcare coordination in Canada).

• 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 policy and eligibility.

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