Document retrieval jobs

Support the Quality Department by reviewing, organizing, scanning, uploading, and maintaining accurate quality records and customer certification packages.

Responsibilities

Review and track Quality Department records, including work orders, travelers, inspection reports, and supporting certifications.
Prepare and review customer certification packages for completeness, accuracy, traceability, and applicable customer requirements.
Perform documentation checks and support internal, customer, and third-party audits by retrieving requested records.
Communicate with internal departments and outside suppliers to resolve missing, incomplete, or incorrect certifications and traveler documentation.
Review nonconformance documentation for completeness and accuracy.

Requirements

High school diploma or equivalent
Nice to have: familiarity with aerospace quality documentation
Nice to have: product traceability

Skills

data entry electronic filing scanning document retrieval Microsoft Office

Generative AI Engineer

Bright Vision Technologies · Posted Nov 3, 2026

Open

Remote, United States +1 more
Remote
Full-time · Senior
$115K–$165K per year
5+ years

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Bright Vision Technologies is seeking a Generative AI Engineer to design and develop applications powered by large language models and other generative models. The role will implement retrieval-augmented generation, prompt and response workflows, model evaluation, and application integrations while addressing accuracy, latency, cost, observability, and responsible-use requirements.

Locations (2)

Irving, Texas, United States
Las Colinas, Texas, United States

Compensation

$115,000–$165,000 Annually

Responsibilities

Build generative AI application components using approved foundation models, model APIs, and orchestration frameworks.
Develop retrieval-augmented generation workflows using document ingestion, chunking, embeddings, and vector retrieval.
Design prompts, structured outputs, tool integrations, and conversation workflows for defined application use cases.
Create evaluation datasets and assess answer quality, relevance, hallucination risk, latency, and cost.
Integrate AI capabilities with enterprise systems and implement logging, monitoring, fallback, and feedback mechanisms.