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Head of AI Integration

Job in Aiken, Aiken County, South Carolina, 29805, USA
Listing for: DBD International
Full Time position
Listed on 2026-09-27
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Business & Operations
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR
Job Description & How to Apply Below

Role summary:

We are looking for a Head of AI Integration to establish and lead DBD's AI capability across our highly regulated markets.

This is a newly created senior role with responsibility for both the technical leadership of AI/ML solutions and the strategic, client-facing development of DBD’s AI proposition. You will define our AI vision and technical standards, build a multidisciplinary team, and work directly with clients to understand their AI ambitions and translate them into practical, trusted and deployable solutions.

Our clients are increasingly exploring AI across areas including resource management, lifecycle mission planning, optimisation and enterprise asset management. You will play a key role in helping them navigate that journey — from early exploration and proof of concept through to validated, production-ready capability.

You will also help establish a repeatable AI methodology and proposition that can extend beyond our existing nuclear programmes into other highly regulated sectors.

What you will be doing:
  • Own and shape DBD’s AI vision, technology strategy and capability roadmap.
  • Act as DBD’s principal AI advisor to clients, assessing their AI maturity and helping them develop realistic adoption roadmaps.
  • Build trusted senior relationships with clients and partners, positioning DBD as a credible AI/ML partner.
  • Lead AI/ML proof-of-concept and demonstration activity, supporting bids and developing proposals where AI capability is a differentiator.
  • Design and apply AI/ML approaches, including machine learning, predictive modelling and, where appropriate, generative AI, to complex lifecycle, mission and operational problems.
  • Provide hands‑on technical leadership using Python and modern AI/ML frameworks and tooling.
  • Set the technical standards for model design, validation, explainability and deployment.
  • Establish robust AI/ML validation, governance and quality assurance standards appropriate to highly regulated and safety‑relevant environments.
  • Advise clients and internal stakeholders on AI tooling, infrastructure and compute requirements, including how DBD’s approach can integrate with partner technologies.
  • Build sustainable AI capability, knowledge and intellectual property within DBD rather than relying on a single individual.
  • Maintain an understanding of our existing physical and process modelling capabilities, identifying opportunities for AI/ML to enhance or integrate with them.
  • Help develop DBD’s AI proposition for opportunities beyond the nuclear sector, particularly within other highly regulated environments.
Formal qualifications or training:
  • Degree in Computer Science, Data Science, Machine Learning or another relevant quantitative or technical discipline.
  • Professional experience applying AI/ML, including leading projects from initial concept through to deployment.
  • Demonstrable experience advising clients on AI adoption, including assessing readiness, shaping adoption roadmaps and supporting the transition to AI‑enabled solutions.
  • Proven senior‑level experience developing client relationships and converting AI/ML opportunities into won work.
  • Strong hands‑on technical proficiency in Python and established AI/ML frameworks and tooling, including familiarity with MLOps practices.
  • Experience leading or managing a technical team.
  • Excellent communication skills, with the ability to translate complex AI/ML concepts into practical recommendations for non‑specialist and senior client stakeholders.
Desirable:
  • M.S. or Ph.D. in a relevant technical discipline.
  • Experience applying AI/ML within process, chemical, engineering or industrial simulation environments.
  • Familiarity with modelling and simulation tools such as gPROMS, OLI or discrete‑event simulation.
  • Experience with open‑source…
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