About the role

What will you do at Glint Tech Solutions?

Job Title: Data / Context Engineer

Location: Remote

Company Overview

Glint Tech Solutions is a women-owned, global IT staffing and recruiting firm supporting enterprise clients across the USA and Canada.

Project Description

A leading enterprise client, a multinational telecommunications technology company, is seeking a Data / Context Engineer to play a pivotal role in shaping how knowledge flows across a massive, multi-region operation. This is a high-visibility opportunity to architect and scale a knowledge base (KB) system that will directly power decision-making across 12 regions and beyond.

The role sits at the intersection of AI infrastructure, data engineering, and real-world business impact, with contributions visible across a nationwide operation from day one.

Key Responsibilities

Sign and implement the multi-regional KB architecture in P1 alongside SA
Seed the KB across 12 regions during P2 (cohort 1 wk1, cohort 2 wk2, cohort 3 wk3 of July)
Build and operate the ingestion pipeline (machine-readable regional standards embeddings retrievable patterns) with sampled human approval gate
Add MOD-specific retrievable context as regional overlays during Sep-Oct
Own KB integrity checks, retrieval evaluation, and weekly health reporting
Mandatory Skills
4-6 years of hands-on RAG / retrieval / vector store engineering in production
Experience building a multi-tenant or multi-region retrieval architecture with overlay / inheritance semantics, not just "one big index"
Vertex AI Vector Search or transferable depth (Pinecone, Weaviate, pgvector with strong tenancy, OpenSearch hybrid)
Embedding model evaluation discipline — retrieval quality metrics (recall@k, precision@k, MRR), not vibes
Python; familiar with structured-doc ingestion pipelines (PDF / XML / spreadsheet chunked, normalized, embedded)
Nice-to-Have Skills
Designed a promotion path between draft/approved/retired patterns with audit log
Sampled human-review workflows integrated with the writeback path
RF / telecom standards format familiarity

Which skills does this role require?

RAGRetrieval engineeringVector store engineeringVertex AI Vector SearchPineconeWeaviatePgvectorOpenSearchPythonData engineeringKnowledge base architectureMachine learningRetrieval evaluationData ingestion pipelinesData EngineeringContext EngineeringRetrieval Augmented GenerationVector SearchVertex AIKnowledge BaseMulti-region architectureData IngestionMachine LearningTelecommunicationsEmbeddingsRetrieval metricsRecall@kPrecision@kMRRStructured-doc ingestionAudit logsTelecom standards

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