Charlotte, NC (Onsite)
AI Experience Engineer will develop and operate AI-enabled portal experiences, agents, workflows, and reusable application components using Agent Marketplace components, approved models, MCPs, and enterprise platform services. This role focuses on building production-ready GenAI and Agentic AI experiences for business users and technology teams.
Key Responsibilities
Design, build, test, and support LLM-powered applications, RAG workflows, agents, and enterprise AI experiences.
Use Software Development Kit, marketplace components, approved tools, MCPs, model routing, guardrails, and observability capabilities.
Develop reusable components, workflows, prompts, APIs, connectors, and integration patterns.
Collaborate with Product Owners, UX, platform engineers, and stakeholders to translate requirements into working AI experiences.
Implement CI/CD, testing, monitoring, troubleshooting, and production support practices.
Follow enterprise security, governance, Responsible AI, and production readiness standards.
Contribute to documentation, demos, knowledge transfer, and reusable delivery patterns.
Required Qualifications
5+ to 8+ years of software engineering or AI application development experience.
5+ years of strong hands-on Python development experience.
5+ years of Experience building LLM applications, RAG solutions, API-based applications, workflow automations, or cloud-native applications.
5+ years of Experience with Git, CI/CD, containers, automated testing, and production troubleshooting.
5+ years of Understanding of prompt engineering, vector search, agentic workflows, and enterprise integration patterns.
Required Skills / Knowledge
Python, LLM frameworks, prompt engineering, RAG, Agentic AI, REST APIs, vector search, Git, CI/CD, containers, Kubernetes, and production support.
Working knowledge of LangChain, LangGraph, Google ADK, MCP concepts, or similar agent development frameworks.
Understanding of guardrails, observability, evaluation signals, and model routing concepts.
Preferred Qualifications
Experience with enterprise AI platforms, internal developer platforms, cloud-native development, or regulated enterprise environments.
Experience with multi-agent architectures, marketplace components, reusable tools, or SDK-based AI development.
Banking or financial services experience.
Expected Outcomes
Production-ready Agentic AI applications and reusable components.
Reliable RAG and agent workflows integrated with enterprise systems.
Improved adoption of SDK, Marketplace, and platform patterns.
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