Remote Data & Knowledge Architect for AI Retrieval Systems

RDMI Tech Ventures; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

RDMI Tech Ventures seeks a data architecture lead to design retrieval-augmented generation and enterprise search architectures. You will shape knowledge graphs, document intelligence, and data quality standards while collaborating with engineers to build reliable retrieval systems for AI workflows.

You will define evaluation metrics, metadata governance, and permissions, and you will mentor teams on scalable data platforms and BI integrations across multi-domain datasets.

Qualifications

• At least four years of experience in data architecture, analytics engineering, search, knowledge management, ML or AI engineering, or business data platforms.
• Experience with SQL, data modeling, APIs, vector databases, document processing, or BI systems.
• Understanding of RAG, embeddings, metadata, permissions, retrieval evaluation, and source grounding.
• Strong architecture documentation and communication skills.

Responsibilities

• Design architectures for retrieval-augmented generation (RAG), enterprise search, knowledge graphs, and document intelligence.
• Define approaches to data quality, source mapping, chunking, metadata, permissions, and evaluation.
• Partner with engineers to implement reliable retrieval and knowledge systems.
• Build benchmarks for answer quality, source grounding, coverage, and business usefulness.
• Advise on data modernization for workflow and revenue intelligence.

Skills

Data architecture

Analytics engineering

Search

Knowledge management

ML/AI engineering

Business data platforms

Architecture documentation

Communication skills

Tools

SQL

Data modeling

APIs

Vector databases

Document processing

BI systems

Pinecone

Weaviate

Qdrant

pgvector

Elasticsearch

Snowflake

BigQuery

dbt

Airflow

Job description

RDMI Tech Ventures seeks a data architecture lead to design retrieval-augmented generation and enterprise search architectures. You will shape knowledge graphs, document intelligence, and data quality standards while collaborating with engineers to build reliable retrieval systems for AI workflows.

You will define evaluation metrics, metadata governance, and permissions, and you will mentor teams on scalable data platforms and BI integrations across multi-domain datasets.