Product Manager – Drilling Solutions AI

The Product Manager, Drilling Solutions AI owns and executes the product roadmap for artificial intelligence capabilities across the Nabors Drilling Solutions technology portfolio. This hands-on role combines product management with rapid solution development: the position identifies high-value drilling and operational use cases, validates them directly by building proofs of concept and working prototypes, and translates validated concepts into scalable product requirements for Engineering and Data Science teams. The role works across Product Management, Engineering, Operations, Commercial, and customer stakeholders to deliver AI-enabled solutions that improve drilling performance, operational efficiency, safety, and customer outcomes. The position applies responsible AI, security, and product governance throughout discovery, prototyping, pilot deployment, commercialization, and continuous improvement.

AI Product Strategy & Roadmap Execution

• Develop and maintain the NDS AI product roadmap for assigned drilling technology platforms and use cases, aligned with business objectives and customer needs.

• Evaluate customer problems, operational workflows, market signals, and technical feasibility to define practical AI product opportunities.

• Prioritize initiatives and backlog items using expected customer value, operational impact, implementation effort, risk, and measurable success criteria.

• Prepare business cases, product briefs, investment recommendations, and product performance updates for leadership review.

Hands-On AI Prototyping & Solution Development

• Personally build proofs of concept, working prototypes, demonstrations, and lightweight AI solutions to validate user needs, data readiness, model behavior, workflow fit, and business value before scaling.

• Use approved development tools, cloud services, APIs, data platforms, low-code tools, scripting languages, and AI frameworks to assemble and test end-to-end solutions.

• Create prompt flows, retrieval and grounding approaches, evaluation datasets, user interfaces, automations, integrations, and analytics needed for functional prototypes.

• Test prototypes with users, document findings and technical limitations, iterate quickly, and recommend whether to stop, refine, pilot, or transition the solution to Engineering.

• Maintain prototype code, configuration, documentation, and reusable components in approved repositories and follow cybersecurity, data-handling, architecture, and responsible AI requirements.

Customer Discovery, Product Definition & Commercialization

• Lead customer and field discovery to understand drilling workflows, decision points, pain points, and adoption barriers, then convert findings into clear product outcomes.