CorrosionRADAR
Asset Integrity Subject Matter Expert (AI Team)
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Location: Based at Cambridge (hybrid) preferred. UK-remote or EU-remote will also be considered.
Based at: Cambridge
Hours of work: 40
Reports to: Head of AI / Engineering
To act as the industry domain expert within the AI team, bringing deep knowledge of Risk-Based Inspection (RBI), asset integrity management, and industrial corrosion programmes. To translate the requirements of industry standards (API 580/581, API 510/570/653, ISO 16708, NACE/AMPP) into AI product features and analytical outputs. To work closely with the AI team to make sure that the predictive models and AI products align with how customers manage their assets in the field, and to support customer engagement by translating the organisation’s AI value into the language and the workflows of asset integrity engineers.
Key Responsibilities
- Working closely with the AI team to provide domain expertise on Risk-Based Inspection, asset integrity management, and industrial corrosion programmes.
- Translate the requirements of industry standards (API 580/581 for RBI, API 510/570/653 for inspection, ISO 16708, ISO 31000, NACE/AMPP corrosion management) into AI product features, acceptance criteria, and validation tests.
- Review and validate the outputs of predictive models, AI algorithms and analytical reports against industry expectations, damage mechanism behaviour, and inspection programme practices.
- Define use cases, give input on the product backlog, support the prioritisation of features, and validate the outputs of the models against real industrial scenarios.
- Engage with customers (asset integrity managers, inspection engineering leads, plant integrity teams) to understand their requirements and to translate the organisation’s AI capabilities into their integrity management workflows.
- Support the development of customer reports and advisory outputs, to make sure they reflect the language, conventions and decision-making logic used by asset integrity professionals.
- Contribute to industry-facing content such as white papers and webinars, to support the brand positioning of the organisation as an intelligent asset integrity provider.
- Maintain awareness of emerging practices in digital integrity management, predictive maintenance, and AI applications in industrial monitoring, and bring these insights back to the AI team.
- Support internal training and knowledge transfer across the AI team, customer success and commercial teams, to share industry domain expertise and to build the wider organisation’s understanding of asset integrity, Risk-Based Inspection and corrosion management.
- Support sales and pre-sales activities with technical and domain expertise when needed.
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Skills And Experience
- 5 to 10 years of industry experience in asset integrity, Risk-Based Inspection, or inspection engineering, at an asset operator or at a major service company (for example Wood, Penspen, ABS Group, DNV, ROSEN, RINA, Bureau Veritas).
- Demonstrable experience in designing, executing or reviewing Risk-Based Inspection programmes for industrial assets (piping, pressure vessels, storage tanks, pipelines).
- Strong working knowledge of API 580 and API 581 (Risk-Based Inspection), API 510, 570 and 653 (inspection codes), ISO 16708 and ISO 31000, and NACE/AMPP corrosion management standards and others.
- Solid understanding of damage mechanisms, corrosion under insulation (CUI), corrosion monitoring techniques, and the integration of monitoring data into inspection planning.
- Industry exposure to oil and gas, petrochemical, refining, power, or other asset-intensive industries.
- Familiarity with corrosion monitoring data, sensor outputs, and the integration of such data into integrity management programmes.
- Working knowledge of digital tools for asset integrity management (for example Meridium, GE APM, Cenosco IMS, Antea, or equivalent RBI software).
- Comfortable working alongside data scientists and software engineers, with the ability to articulate domain knowledge in a way that can be operationalised in algorithms.
- BSc or MSc in engineering (mechanical, materials, chemical, or related discipline).
- Professional certifications such as API 580 (Risk-Based Inspection Professional), API 510/570/653 inspector certifications, NACE/AMPP corrosion certifications, or ASNT/PCN/ISO 9712 NDT certifications are highly desirable.
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About You
- Ability to translate complex industry standards and asset integrity practices into clear product requirements for an AI and data science team.
- Excellent communication skills to bridge between technical audiences (AI, data science, software) and applied audiences (asset integrity engineers, plant managers, inspectors).
- Customer-facing mindset, with experience of presenting and advising at engineering and management levels in industrial environments.
- Self-managed and proactive, comfortable working in a cross-functional environment that spans engineering, AI, customer success, and commercial functions.
- Eagerness to learn AI and data science concepts and apply them to industry problems.
- Willing to travel internationally for customer engagement, industry events and conferences when needed.
- Fluent English, both written and spoken.
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