AI Experience Engineer
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.