Our Company

Abyss Solutions is reinventing industrial asset management both above and underwater for step-change improvements in; asset life, maintenance cost, and reduction of failure risk. Think oil rigs, dam walls, ship hulls, any asset subject to deterioration in water and weather.

We do so utilizing extremely sophisticated, unique (and patented) Artificial Intelligence/ Machine Learning software together with a deep understanding of our customers’ asset integrity needs and processes. Creating a 3D ‘digital twin’ of customer assets. Using drones and Abyss analytics is just the beginning, Abyss comprehensively classifies the ‘state’ of the asset to identify exactly what maintenance is required, providing precise direction.

Purpose & Scope

The Quality Specialist owns and drives quality across live data processing and operational environments, acting as the central authority for the organization’s Quality Management System (QMS). This role is responsible for implementing and continuously improving internationally recognized quality and management standards, i.e., ISO 9001, ISO 42001, and other applicable standards, embedding risk-based controls, and driving Total Quality Management (TQM) practices to ensure consistent delivery quality and operational efficiency. Working closely with Operations, Data, Engineering, Product, and other cross-functional stakeholders, the Quality Specialist ensures the accuracy, consistency, and reliability of data-driven asset intelligence, while reducing defects and rework, strengthening operational efficiency, and driving a culture of accountability, continuous improvement, and quality ownership.

Tasks

Quality Systems, Standards & Compliance

• Implement, maintain, and continuously evolve the Quality Management System (QMS) aligned quality standards.
• Ensure quality standards are embedded across live data processing and operational workflows.
• Develop, maintain, and govern quality guidelines, quality frameworks , and quality document control systems.
• Apply risk-based thinking to adjust controls, sampling, and inspection rigor based on performance trends.

Operational Quality & Incident Management

• Monitor live quality across point cloud processing, data registration, outputs, and operational workflows while addressing deviations proactively before they impact deliverables.
• Own and execute NCR, incident reporting, and CAPA cycles end-to-end.
• Conduct structured Root Cause Analysis (RCA) using methodologies such as 5 Whys and Fishbone.
• Identify systemic causes of defects, rework, and process failures and drive sustainable corrective actions.
• Collaborate with technical and operational teams to identify recurring quality issues, implement preventive controls and improve systemic quality.
• Demonstrate empathy and a proactive mindset when engaging with teams during quality issues.

Quality Frameworks & TQM

• Execute wider quality initiatives aligned with enterprise and product strategy.
• Drive Total Quality Management (TQM) principles across data capture, processing, and delivery teams.
• Lead quality improvement initiatives to reduce defects, rework, and Cost of Poor Quality (COPQ).
• Promote a culture where quality is treated as a shared responsibility along the process, not simply a final-stage inspection activity.

Training, Capability Building & Team Support

• Nurture, mentor, and support the QA team, strengthening quality ownership at all levels.
• Develop and deliver practical quality-related training, including ISO awareness, RCA, CAPA, and process adherence.
• Build awareness and organizational capability in quality thinking, risk awareness, and preventive controls.

Process Improvement & Reporting

• Analyze quality data, KPIs, and trends to translate data into actionable improvement initiatives.
• Develop quality dashboards, reports, and performance metrics for management review.
• Lead quality improvement projects and initiatives to enhance efficiency and reduce defects.

Knowledge Requirements

• QMS implementation and ISO 9001:2015
• Quality documentation and document control
• NCR, incident management, CAPA, and RCA methodologies
• Total Quality Management (TQM) and continuous improvement methodologies
• Risk-based thinking in operational and data-driven environments
• Exposure to point clouds, AI/ML, digital twins, or visual data processing is highly desirable

Skills & Competencies

• Strong quality ownership, proactive and attention to detail mindset with enterprise-level accountability
• Expertise in live operations, data processing quality assurance or risk management
• Excellent RCA, CAPA execution, and incident learning facilitation
• Ability to translate and conduct quality requirements into practical operational controls
• High empathy, proactive problem-solving, and stakeholder influence
• Strong cross-functional communication and collaboration skills
• Analytical, data-driven decision-making capability and problem-solving approach

Qualifications & Experience

• Bachelor’s degree in Engineering, Quality Management, AI/ML, data science or a related discipline
• 4-8 years of experience in quality management, quality assurance, or operational quality within live operations, engineering, technology, or data processing environments.
• Proven experience implementing and operating ISO certified QMS standards
• Experience conducting, NCR/CAPA management, RCA and quality improvement initiatives
• Exposure to point clouds, AI/ML, digital twins, or visual data processing will be an advantage.