Deployment Strategist

About the role

Turn industrial problems into AI solutions. At Foresight Data Machines (FDM), we’re building AI systems for some of the world’s most complex industrial environments. Our flagship product, ScrapChef, combines AI, physics and industrial data to optimise steelmaking—helping major producers make better decisions around scrap purchasing, material mixes and furnace operations. As a Deployment Strategist you’ll sit at the intersection of our technology, our customers and the physical world—turning complex industrial challenges into opportunities for AI to create measurable value.

Responsibilities

• Work directly with customers inside major industrial facilities.
• Understand complex operational, commercial and technical problems.
• Identify where AI and optimisation can create meaningful value.
• Translate customer problems into clear technical requirements.
• Collaborate with engineers, AI researchers, physicists and plant operators.
• Lead deployments from initial discovery through to production.
• Analyse operational data and communicate insights to customers.
• Drive adoption, measure impact and continuously improve solutions.

Qualifications

• Strong analytical and problem‑solving ability.
• Excellent communication and stakeholder‑management skills.
• Ability to understand complex technical concepts.
• Highly curious and commercially minded approach.
• Ability to operate independently in ambiguous environments.
• Willingness to spend significant time with customers on‑site.
• Industry experience is not required; focus is on problem‑understanding, clear communication, and outcome delivery.

Preferred backgrounds

• Strategy or management consultant.
• Technical consultant.
• Product manager.
• Solutions engineer.
• Data scientist.
• Industrial or process engineer.
• Operations specialist.
• Engineer with strong customer‑facing experience.
• High‑performing generalist with exceptional analytical ability.

Benefits

• Real‑world impact—deploy technology that influences steel purchasing, processing and production decisions worth millions of dollars.
• Exceptional problems—work at the intersection of AI, physics, optimisation, software and heavy industry.
• Customer ownership—direct interaction with senior stakeholders and plant teams, responsible for turning technology into measurable commercial outcomes.
• Technical exposure—collaborate with software engineers, AI researchers and physicists, gaining deep understanding of cutting‑edge AI systems.
• Extreme ownership—small team, minimal bureaucracy, significant autonomy to shape deployments and company scaling.
• Early‑stage opportunity—backed by investors, offering disproportionate impact for exceptional contributors.