• Learn new technologies and architectures, including work with uniform data layers, integrations with contact center providers, and new product development. • Work with leadership to bring your engineering experience to the table and ideate new features and functionality. • Design, build, and maintain Python-based backend services that orchestrate AI agent workflows using LangChain and LangGraph. • Contribute to the development of a multi-tenant simulation platform handling high volumes of concurrent AI-driven conversations in a public cloud environment. • Integrate with contact center providers (such as LivePerson) and external LLM providers through a unified gateway abstraction. • Build and extend REST APIs using the Litestar framework, following strong typing and Pydantic-based data modeling patterns. • Work with Couchbase for conversation state persistence, implementing optimistic concurrency patterns (CAS locking) for correctness in multi-pod deployments. • Write high-quality, well-tested code with a focus on behavior-driven unit and integration testing.