Altana AI
Product Expert, PLM and ERP
$200K–$255K
Brooklyn, NY +3 · Full-time · Posted Apr 28, 2026
- Location
- Brooklyn, NY
Washington, DC
Brooklyn, NY
Washington, D.C. - Experience
- 5+ years; the posting describes hands-on PLM and/or ERP experience in preferred qualifications, while the core profile asks for experience with PLM and ERP systems.
About the job
Own product strategy for Altana’s Product Passports, connecting PLM, ERP, and trade data so product information flows accurately across manufacturing, shipping, and customs compliance.
What you'll do
- Define product workflows and data models that reconcile product bills of materials and propagate changes across commercial documents and regulatory filings.
- Identify and prioritize automation and integrations that reduce manual product-to-trade data handoffs.
- Collaborate with customers, engineering, and government-facing teams; use AI tools, prototypes, and demos to test and communicate product concepts.
What they ask for
- 5+ years working with PLM and ERP systems in an enterprise manufacturing, sourcing, or trade compliance context.
- Understand the product-to-shipment data chain, including SKUs, bills of materials, purchase orders, invoices, advance ship notices, and customs entries.
- Comfortable discussing data structures, API design, and integration architecture with engineers.
- Actively use AI tools in work to draft, prototype, analyze, or explain.
Nice to have
- Experience with SAP, Oracle, Teamcenter, Windchill, Arena, or equivalent; and familiarity with BOM structures, product documents, and PLM-ERP integrations.
- Experience in data modeling, integration architecture, enterprise system implementation, product management, business analysis, or enterprise technology strategy.
Pay
$200,000 - $255,000 USD (annual base salary)
Tools
SAP, Oracle, Teamcenter, Windchill, Arena, API
AI focus
Use AI tools to prototype workflows, generate explanations, and test ideas; explore automation and machine learning for extracting BOM data, reconciling product variants, recommending classifications, and flagging origin risks.
Model-written summary · the original posting is authoritative