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Open nowFirst seen 39 hours ago

Data / Context Engineer

Glint Tech Solutions LLC139 open roles

Where
Texas, United States, Remote
Work mode
Remote
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Your applicationOpen nowData / Context EngineerGlint Tech Solutions LLC · Texas, United States, Remote

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  6. 45.1%60 days
This job: first seen 39 hours ago

The posting

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
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