to design, develop, and maintain RAG-based systems that power intelligent enterprise solutions. The ideal candidate will work within an existing RAG framework, take ownership of critical modules, and seamlessly integrate AI solutions with business tools such as CRMs and email platforms.
This role involves deploying
Model Context Protocol (MCP) servers
, adapting to an evolving, event-driven, horizontally scalable architecture, and ensuring production-quality code with rapid prototyping capabilities.
Key Responsibilities:
Build and maintain Retrieval-Augmented Generation (RAG) pipelines
Take ownership of individual modules within an existing RAG framework
Deploy and manage
MCP (Model Context Protocol)
servers
Integrate AI solutions with enterprise tools like
HubSpot, CRMs, email systems
, and internal data sources
Work with event-driven and horizontally scalable backend architectures
Prototype quickly while writing clean, maintainable, production-ready code
Contribute to evolving system design and data architecture
Technical Skills Required:
Primary:
Strong experience with
LlamaIndex
(preferred over LangChain) for building RAG pipelines
Hands-on experience with complex
RAG architectures
integrating 10-12 heterogeneous data sources
Familiarity with automation and building actionable AI-driven workflows
Experience integrating with
CRM systems (e.g., HubSpot)
, email platforms, and APIs
Solid understanding of scalable backend development and cloud deployments
* Bonus: Experience in event-driven architecture, microservices, and AI product engineering
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