RAG Engineer

Sumeru Global Technologies Private Limited

Jersey City, NJ, United States

2 months ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

2 years minimum

Compensation

$120,000.0 - $200,000.0

Working hours

Regular working hours

Job source

indeed.com

Tech stack

Java (Programming Language) .NET Framework Application Programming Interfaces (APIs) Artificial Intelligence Audit Trail Microsoft Azure Cloud Storage Encodings Databases Continuous Integration Information Engineering Data Governance

+13 more

Data Security Elasticsearch Graph Database Python (Programming Language) Node.Js Parsing Role-Based Access Control Standard Sql Search Technologies Management of Software Versions Indexer Backend Search Engines

Job description

· Build document ingestion, parsing, chunking, metadata extraction, embedding, indexing, and versioning pipelines.

· Implement RAG services using vector search, keyword search, hybrid retrieval, metadata filters, reranking, and citations.

· Integrate with Azure AI Search, pgvector, Pinecone, Weaviate, Qdrant, Milvus, Elasticsearch, OpenSearch, or similar platforms.

· Build APIs for retrieval, source traceability, ingestion status, feedback capture, and citation support. Implement permission-aware retrieval, RBAC, tenant isolation, audit logging, PII handling, and secure data access.

· Support retrieval quality evaluation, grounding, hallucination reduction, client demos, UAT, and production readiness.

Requirements

Do you have experience in Search engines?, · Strong backend/data engineering using Python, Java, Node.js, or .NET. Strong SQL and database experience.

· Minimum 2 years hands-on AI/RAG implementation experience.

· Experience with embeddings, vector search, hybrid search, document ingestion, and RAG pipelines. Experience with Azure AI Search, pgvector, Pinecone, Weaviate, Qdrant, Milvus, Elasticsearch, OpenSearch, or equivalent.

· Understanding of chunking, retrieval tuning, reranking, context assembly, citations, and retrieval evaluation. BFSI, banking, insurance, capital markets, payments, or regulated enterprise experience. Client implementation experience.

· Preferred Skills

· Azure Blob Storage, Azure AI Search, Azure Document Intelligence, Azure OpenAI, or similar Azure services.

· Experience with data governance, document lineage, metadata models, knowledge graphs, or ontology-driven retrieval.

· Experience with CI/CD, containers, observability, and secure cloud deployment