The AI Agent Developer joins the Data & Analytics organization within the Corporate Payments division, specifically supporting the Account Payables line of business. As an individual contributor, you will design, develop, and deploy enterprise AI Agents to solve operational challenges. You will build intelligent solutions using large language models, agentic AI frameworks, and workflow automation to support Payables Operations. Key responsibilities include creating RAG solutions, managing vector stores, and integrating agents with APIs and databases. You will utilize technologies such as Python, SQL, OpenAI, Azure OpenAI, Claude, and Microsoft Fabric. Additionally, you will establish reusable development patterns, provide training, and coach functional teams to build their own agents. This role focuses on moving AI from business ideas to production while managing security, governance, and risk.
Design, develop, test, and deploy enterprise AI agents and LLM-powered applications for Payables business needs.
Build RAG solutions using company documents, databases, knowledge repositories, and vector stores.
Create agentic workflows that retrieve information, call APIs, use tools, and connect to company systems.
Develop reusable AI components, templates, frameworks, and development patterns to scale solutions.
Create training materials and documentation to enable functional teams to build their own AI agents.
Establish automated evaluation methods to measure accuracy, relevance, cost, and task success.
Implement security guardrails, authentication, and governance to mitigate risks like hallucinations and data leakage.
Monitor live agents using telemetry and business KPIs to investigate failures and implement reliability fixes.
What we're looking for
Bachelor’s degree in Computer Science, Information Systems, AI, Data Science, Engineering, or a related field, or equivalent professional experience.
3+ years of relevant experience in AI application development, automation, machine learning, data engineering, software development, or a related technical discipline.
Demonstrated hands-on experience building AI, LLM-powered, automation, or intelligent application solutions.
Strong application-development skills using Python and experience working with REST APIs, JSON, SDKs, authentication mechanisms, and enterprise integrations.
Experience working with one or more LLM platforms or APIs such as OpenAI, Azure OpenAI, Anthropic, Gemini, or comparable technologies.
Experience designing or implementing Retrieval-Augmented Generation, embeddings, semantic search, document retrieval, vector search, or other enterprise knowledge-grounding solutions.
Working knowledge of relational databases and SQL sufficient to enable AI applications to securely consume, investigate, and reason across structured enterprise data.
Strong understanding of software engineering practices including modular design, debugging, testing, version control, Git, code review, deployment, and production support.