Agentic AI Lead (Python)

Cloudious LLC

Job Location:

Berkeley Heights, NJ - USA

Monthly Salary: Not Disclosed

Posted on: 11 days ago

Vacancies: 1 Vacancy

Job Summary

Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking embeddings indexing retrieval reranking grounding).
Build agentic workflows (tool use planning reflection/guardrails structured outputs) using Python-first frameworks.
Integrate agents with Graph DBs (e.g. Neo4j JanusGraph Neptune) and Vector DBs (e.g. Vertex Vector Search Pinecone Weaviate Milvus pgvector).
Create robust data ingestion/ETL from PDFs docs webpages and internal sources; implement metadata strategy and access control.
Define and run evaluation (retrieval metrics answer quality hallucination/grounding checks) and improve system quality iteratively.
Ship to production: APIs monitoring/observability cost/performance optimization CI/CD and security best practices.

Must-have skills

Strong Python (clean architecture async testing typing packaging).
Proven experience building RAG solutions (hybrid search reranking chunking strategies embeddings prompt schema design).
Hands-on with Vertex AI and GCP fundamentals (IAM logging/monitoring Cloud Run/GKE storage).
Experience with at least one agentic framework (e.g. LangGraph/LangChain LlamaIndex Semantic Kernel AutoGen) and tool/function calling patterns.
Solid knowledge of vector search concepts and at least one vector DB in production.
Comfortable with graph data modeling and graph querying (Cypher/Gremlin/SPARQL basics).
Strong engineering practices: code reviews testing telemetry secure-by-design reliability mindset.

Design and implement RAG pipelines on Google Cloud / Vertex AI (chunking embeddings indexing retrieval reranking grounding). Build agentic workflows (tool use planning reflection/guardrails structured outputs) using Python-first frameworks. Integrate agents with Graph DBs (e.g. Neo4j JanusGra...