ASC Global
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About this role
(Build & Scale Our AI-Driven Global Sourcing Platform)
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.
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.
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
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
Beyond that: measurable hours saved, faster sourcing turnaround, broader AI adoption across departments, and a documented plan for scaling to hundreds of sources
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
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
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