The role involves building production-ready multi-agent workflows that integrate tools like APIs, ERPs, and CRMs with robust error handling
Job Summary
The role involves building production-ready multi-agent workflows that integrate tools like APIs, ERPs, and CRMs with robust error handling.
Candidates will design and maintain end-to-end RAG pipelines for ingestion, chunking, embedding, and retrieval evaluation to serve as knowledge backends.
This position requires developing hybrid automation solutions where AI agents hand off tasks to RPA bots with seamless exception handling.
Matching Summary
The role involves building production-ready multi-agent workflows that integrate tools like APIs, ERPs, and CRMs with robust error handling.
Skills & Requirements
Must-have
LangChain or LangGraph experience
End-to-end RAG pipeline development
Python programming proficiency
RPA platform integration skills
LLM API implementation expertise
Nice-to-have
LoRA or QLoRA fine-tuning knowledge
Agent observability tooling experience
Cloud AI certification credentials
Vector database optimization skills
Prompt engineering best practices
Key Requirements
2-5 years software engineering experience
Bachelor's or Master's in CS, AI/ML, or Data Science
Proven delivery of complete AI automation solutions in production