RAG + Agentic AI Lead

Job Description

REQUIREMENTS

• 7+ years of experience in software engineering or AI/ML roles
• Deep expertise in RAG pipeline engineering and production deployment
• Hands-on experience with LangGraph and agentic workflow development
• Proficiency with vector search systems such as Qdrant, Weaviate, or OpenSearch
• Strong Python programming skills and FastAPI microservices development
• Experience with LLM operations, prompt engineering, and hallucination control
• Background in building document ingestion and ETL pipelines
• Knowledge of multi-agent orchestration and tool-calling workflows
• Understanding of security best practices and PII handling in AI systems
• Proven team leadership and mentoring experience

Preferred

• Experience with Haystack, LlamaIndex, or other RAG frameworks
• Fine-tuning retrievers or small LLMs for domain-specific use cases
• Ontology modeling and enterprise search deployment experience
• Background deploying agents in customer support, operations, legal, or engineering contexts

RESPONSIBILITIES

• Build end-to-end RAG pipelines including smart chunking, hybrid retrieval, reranking, and query rewriting
• Implement LangGraph-based agentic workflows with tools, planning, and self-healing behaviors
• Develop and optimize vector search systems using Qdrant, Weaviate, or OpenSearch
• Design multi-tenant, ontology-driven knowledge layers for enterprise data
• Implement guardrails, hallucination reduction, and automated evaluation frameworks
• Build and maintain document ingestion pipelines for PDF, DOCX, OCR, and images
• Architect and deploy FastAPI-based AI microservices with caching and async execution
• Integrate LLM systems with enterprise applications including SharePoint, CRM, and databases
• Ensure security, PII safety, auditability, and governance requirements are met
• Lead and mentor a team of AI/ML engineers with technical guidance and code reviews

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