AI Agent Developer

What We Need Corpay is currently looking to hire an AI Agent Developer within our Corporate Payments division. This position falls under our Account Payables line of business. In this role, the AI Agent Developer is an experienced individual contributor within Corpay Payables' Data & Analytics organization and AI Center of Excellence (AI CoE), responsible for designing, developing, deploying, and continuously improving enterprise AI Agents that solve real-world business and operational challenges across the Payables division. This role will help expand Corpay's AI development capabilities and increase the velocity at which AI Agents move from business idea to production implementation. The AI Agent Developer will build intelligent solutions using large language models (LLMs), agentic AI frameworks, enterprise data, APIs, tools, and workflow automation to support use cases across Payables Operations and other functional areas. In addition to directly developing AI Agents, this role will help build AI capability across the organization by creating reusable development patterns, standards, training, and hands-on education that enable designated team members within functional areas to independently design, build, test, and implement AI Agents for their respective business needs. The ideal candidate combines strong software and AI engineering capabilities with practical business judgment. This individual must be comfortable working directly with business stakeholders, translating ambiguous problems into well-defined AI solutions, rapidly prototyping new capabilities, and applying the engineering, security, governance, evaluation, and operational discipline required to move AI solutions into reliable production use. How We Work As an AI Agent Developer you will be expected to work in an onsite environment reporting to either our Brentwood, TN or Peachtree Corners, GA office location. Corpay will set you up for success by providing: • Assigned workspace in our Brentwood, TN and Peachtree Corners, GA office location • Company-issued equipment • Formal, hands-on training Role Responsibilities The responsibilities of the role will include: • Designing, developing, testing, deploying, maintaining, and improving enterprise AI agents and LLM-powered applications for Payables business and operational needs. • Partnering with business teams to understand processes, identify AI opportunities, gather requirements, and turn needs into technical solutions. • Building AI agent workflows that can retrieve information, use data, call APIs and tools, complete tasks, and securely connect with company systems. • Developing solutions using LLMs and enterprise AI platforms such as OpenAI/ChatGPT, Azure OpenAI, Copilot Studio, Microsoft Fabric, Claude, or similar tools. • Building RAG solutions using company documents, databases, knowledge repositories, vector stores, and approved data sources. • Connecting AI agents with company applications through APIs, databases, SDKs, MCP-compatible services, connectors, and other integration methods. • Creating effective prompts, system instructions, context strategies, tool definitions, structured outputs, and multi-step agent workflows. • Deciding when to use AI, business rules, traditional software, workflow automation, or human review within a process. • Creating reusable AI components, templates, frameworks, connectors, testing methods, and development patterns. • Establishing standards and repeatable practices that help AI solutions scale across Payables. • Creating training materials, examples, documentation, and learning experiences for functional teams. • Coaching and guiding Payables team members as they begin building AI agents for their own areas. • Supporting teams in following architecture, security, evaluation, governance, and development standards while enabling safe self-service AI development. • Reviewing and advising on agents built by functional teams to ensure they meet production-readiness and responsible-AI standards. • Creating automated and human evaluation methods for measuring accuracy, relevance, completeness, task success, response time, cost, and user satisfaction. • Developing test cases, golden datasets, regression tests, and other methods for consistently assessing agent behavior. • Identifying and reducing AI risks such as hallucinations, incorrect tool use, incomplete retrieval, prompt injection, inappropriate actions, and data leakage. • Implementing validation, grounding, guardrails, permissions, authentication, authorization, human review, and escalation processes based on risk. • Protecting confidential company information and following Corpay security, privacy, governance, and responsible-AI standards. • Optimizing AI solutions for performance, token use, response time, cost, reliability, scalability, and user experience. • Testing new AI capabilities through proofs of concept and rapid prototypes to determine business value and production readin