AI Automation & Data Platform Lead
关于 ASC 全球，ASC 全球是一家全球独立的分销商和采购公司，服务于电子元件，计算机和数据中心，工业 MRO 和航空 MRO 市场。我们从世界各地供应商那里获得半导体，被动组件，互联产品，内存，电脑硬件，数据中心基础设施和工业/航空零部件。机会 我们正在建立一个人工智能驱动的全球采购和产品智能平台，我们需要有人能够构建它并帮助其余公司将 AI 投入使用。这是一种罕见的混合物：你将个人构建和运输一个系统，它不断监测数百个分销商网站，经纪人库存，市场和制造商来源 - - 识别产品，捕捉价格和可用性，并与规范部件匹配列表 - - 并直接与我们的买家，销售，运营和领导层合作，在整个公司找到和实施实用的 AI 使用案例。这不是你交给其他人要求的角色，然后等待。你会编写代码，部署系统，并且还运行让人们使用它的研讨会。你会做什么？· 建立和运营爬行，数据摄入，正常化和匹配平台 -处理静态和 JavaScript 染的网站，PDF 文件，页面化和多语言内容，每张记录都具有完整源来源 ·设计可行的产品/供应商/提供数据模型以及与列表相符的实体分辨率逻辑 ·使用 LLM,它们真正帮助 （提取，翻译，分类）对适当评估，信任门和人力审查-永远不要让模型猜测价格或数量它无法找到 ·将平台连接到 Zoho CRM 的 RFQ 工作流，并向下流，QuickBooks. ·与销售，采购，运营和金融合作发现 AI 或自动化可以改善的其他流程，将这些转变为真正的飞行员，培训员工使用它们并跟踪影响 成功看起来像什么？•在最初90天内建立一个工作架构和数据模型 ·至少10个源头连接到完全来源 ·可搜索，正常化的产品和供应商数据 ·测量匹配精度 ·实行源健康监控 ·初步 Zoho mea RFQ 集成 ·此之外：
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This is a remote position.
AI Automation & Data Platform Lead
(Build & Scale Our AI-Driven Global Sourcing Platform)
About ASC Global
ASC Global is a global independent distributor and sourcing company serving the electronic-components, computer and data-center, industrial MRO and aviation MRO markets. We source semiconductors, passive components, interconnect products, memory, computer hardware, data-center infrastructure and industrial/aviation parts from suppliers worldwide.
The Opportunity
We're building an AI-driven global sourcing and product-intelligence platform, and we need someone who can both build it and help the rest of the company put AI to work. This is a rare hybrid: part hands-on technical builder, part AI/automation lead for the business. You'll personally architect and ship a system that continuously monitors hundreds of distributor sites, broker inventories, marketplaces and manufacturer sources - identifying products, capturing pricing and availability, and matching listings to canonical parts - while also working directly with our buyers, sales, operations and leadership to find and implement practical AI use cases across the company.
This is not a role where you hand requirements to someone else and wait. You'll write the code, deploy the system, and also run the workshops that get people using it.
What You'll Do
- Build and operate the crawling, data-ingestion, normalization and matching platform - handling static and JavaScript-rendered sites, PDFs, pagination and multilingual content, with full source provenance on every record
- Design the canonical product/supplier/offer data model and the entity-resolution logic that matches listings to real parts
- Use LLMs where they genuinely help (extraction, translation, classification) with proper evaluation, confidence thresholds and human review - never letting a model guess a price or quantity it can't find
- Connect the platform to Zoho CRM's RFQ workflow and, downstream, QuickBooks
- Work with Sales, Purchasing, Operations and Finance to spot other processes AI or automation can improve, turn those into real pilots, train employees to use them, and track the impact
What Success Looks Like
- A working architecture and data model within the first 90 days
- At least 10 sources connected with full provenance
- Searchable, normalized product and supplier data
- Measured matching accuracy
- Source-health monitoring in place
- An initial Zoho RFQ integration
- Beyond that: measurable hours saved, faster sourcing turnaround, broader AI adoption across departments, and a documented plan for scaling to hundreds of sources
What We're Looking For
- Five or more years of hands-on software/data-engineering experience with real production ownership of web-crawling or large-scale data-acquisition systems - not personal projects or coursework
- Advanced Python and strong SQL
- Experience with a production crawling framework (e.g. Scrapy) and browser automation (Playwright or Selenium) for JavaScript-rendered sites
- Solid grounding in HTTP, rate limiting, retries, queues and failure recovery
- Experience building normalized pipelines from messy, conflicting data, plus entity resolution / fuzzy matching / deduplication work backed by real accuracy numbers
- Strong PostgreSQL (or similar), plus Docker and at least one major cloud platform
- Comfortable using LLM APIs in production - structured outputs, evaluation, cost control - without treating them as a replacement for deterministic checks
- Personally implemented an AI or automation solution inside a real company (not just used the tools), ideally across more than one department, and comfortable running training and translating business needs into requirements for other engineers
Nice to Have
- Temporal, Dagster, Prefect or Airflow
- OpenSearch or Elasticsearch
- RapidFuzz, Splink or embeddings-based matching
- Zoho, Salesforce, HubSpot, QuickBooks or other ERP integrations
- Electronic components or other complex technical catalogs
- Prior experience as the first or lead engineer on a new platform
Originally posted on Himalayas