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Analyst, AI Engineer

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About WAI

Since 1978, WAI has grown from an entrepreneurial start-up into a global aftermarket leader headquartered in South Florida. Nearly five decades of product knowledge, customer trust, and operational scale now support an ambitious growth agenda across distribution, manufacturing, product, customer, supply chain, and shared-service operations.


That scale creates a meaningful opportunity for practical enterprise AI. WAI is investing in AI, automation, data, and digital capabilities that can improve how work gets done: reducing manual effort, increasing speed and quality, strengthening decision-making, and helping teams serve customers more effectively.


About the Role

WAI is expanding its enterprise AI capabilities with a focus on trusted data, intelligent retrieval, and practical AI solutions that improve how employees access information and get work done.


The Analyst, AI Engineering is an offshore technical role that supports WAI's internal AI capability by helping build AI-ready data access, catalog intelligence, document ingestion, retrieval workflows, AI assistant capabilities, and continuous improvement processes. The role works under the direction of AI platform leadership and partners with IT, business-facing AI automation resources, data owners, and other technical contributors.

This role provides hands-on build capacity for approved AI and data work, including Infor integration support, catalog vector search, document parsing, RAG workflows, chatbot telemetry, open-source model evaluation, testing, documentation, and production support activities. The role is not intended to own business prioritization or the overall AI operating model.


What you'll do

  • Build and support AI-ready access to WAI catalog, customer, order, product, sales-channel, and related business data as directed by AI platform leadership.
  • Assist with Infor integration and other trusted data connections so AI outputs are grounded in approved business data sources.
  • Implement semantic, keyword, and structured search across catalog, OE number, fitment, cross-reference, technical specification, and product data.
  • Parse and structure PDFs, Excel files, fitment guides, manufacturer specifications, RMA forms, customer questions, chatbot conversations, and other technical or business documents.
  • Build and support retrieval-augmented generation (RAG), embeddings, vector search, document ingestion pipelines, prompt workflows, and AI assistant capabilities for internal users and distributor support.
  • Capture and organize real user questions, failed searches, corrections, successful answers, and feedback to support evaluation data, retrieval improvement, and future model tuning.
  • Assist with evaluating, deploying, and testing approved hosted or open-source models such as Llama, Mistral, Qwen, or similar models under technical direction.
  • Support AI workflows related to Amazon Business trends, listing performance, returns, customer demand, and other approved business intelligence use cases as assigned.
  • Document technical logic, data mappings, prompts, retrieval sources, test cases, known issues, and support procedures.
  • Test AI outputs for source grounding, accuracy, consistency, reliability, and alignment with acceptance criteria.
  • Monitor assigned workflows, troubleshoot defects, analyze failures, and recommend improvements to retrieval quality, data quality, model behavior, and workflow performance.
  • Collaborate with offshore and onsite team members, IT, data owners, and business-facing AI resources to deliver approved work within WAI standards.

Undertakes additional responsibilities and tasks as directed by management.

Skills

See also

AI Engineering jobs by country — openings, pay and top skills →

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