Test Automation Engineer

For nearly 40 years, PDI has helped convenience retailers and petroleum wholesalers adapt to changes in the industry by leveraging the latest technologies. Simplifying the complexity in your world is our main focus. That's why we're delivering an integrated portfolio of global, cloud based solutions and services to meet our customers needs today and well into the future. From the back office to fuel logistics, and the latest wave of consumer demands and digital commerce, PDI solutions and services are designed to give you a competitive edge. Our deep domain knowledge is backed by our industry-specific software offerings and a people-first approach. Serving the entire supply chain means that we’ve had to solve a wide range of industry challenges and deliver measurable value. To address the increasingly dynamic convenience retail and petroleum wholesale industry, PDI leads the way with converged digital, cloud-optimized, secure, and scalable solutions including ERP, Loyalty, Fuel Pricing, Point-of-Sale and Logistics to create a broader industry ecosystem. The result is unparalleled insights, simplified operations, and higher profitability for your employees and business. We’re dedicated to helping our more than 1,500 customers in over 50 countries, providing solutions and services to over 200,000 sites.

Job Responsibilities:

• AI Platform Architecture & Implementation: Design, build, and deploy intelligent AI-driven platform capabilities that enable automation, intelligent insights, and advanced decision-making across distributed services and data systems.
• Product Innovation: Drive the development of next-generation AI-enabled platform features that enhance operational efficiency, enable intelligent automation, and deliver scalable, high-performance digital experiences.
• Generative AI Integration: Seamlessly integrate generative AI capabilities into platform services, including prompt engineering, Retrieval-Augmented Generation (RAG), intelligent workflows, and contextual reasoning systems.
• Intelligent System Leverage: Utilize Large Language Models (LLMs), embeddings, and vector-based retrieval systems to build intelligent, context-aware solutions that enhance platform capabilities and automation.
• AI Quality & Evaluation: Develop frameworks and methodologies for validating AI system performance, including response accuracy, model reliability, safety evaluation, and output consistency.
• AI Testing & Validation: Design and implement automated validation strategies to ensure reliability and correctness of AI-driven features, including automated test generation, model evaluation, and workflow validation.