Our client is a fast-growing AI enterprise startup seeking a Forward Deployed Product Manager to own customer engagements end-to-end — from messy problem discovery through deployment, adoption, and measurable business impact in heavy industry environments.
This is a high-ownership, customer-facing role for someone who combines deep domain expertise in oil & gas, utilities, or chemicals with the product and delivery skills to turn complex operational workflows into shipped AI-powered solutions.
What You'll Do
Own customer engagements end-to-end — from problem discovery through deployment, adoption, and measurable business impact
Build credibility with customer stakeholders across field teams, technical teams, executives, and commercial buyers through deep domain fluency
Translate complex customer workflows into clear problem statements, MVP scope, data requirements, user stories, and product requirements
Partner with engineering and design to turn customer needs into stable, extensible AI-powered solutions
Drive pilot-to-production conversions by creating so much value customers cannot live without the product when the pilot ends
Manage tradeoffs across customer urgency, technical complexity, commercial value, and long-term product reuse
Identify repeatable patterns across engagements and shape them into scalable product and delivery processes
Stay close to expansion, renewal, and commercial outcomes — with significant variable bonus tied to account growth
Key Requirements
5+ years in customer-facing, high-ownership roles — consulting, forward-deployed product, or enterprise delivery
Heavy industry domain exposure — oil & gas, utilities, chemicals, or refining as an operator, engineer, or consultant
Consultative engagement ownership — has run customer engagements and connected them to commercial outcomes
Product experience — writing tickets, working with engineering and design
MBA from a top program (Harvard, Tuck, Stanford, Haas, Wharton, Booth, Kellogg) preferred
MBB or Palantir-type forward-deployed product experience preferred
Startup experience preferred
Hands-on familiarity with AI tools (Claude, LLMs) in day-to-day work