Overview

WSP is seeking an Engineer AI (Mining Automation) to join the GCC Specialist Mining Services team, supporting the delivery of digital and automation solutions for global mining projects.

Responsibilities

• Design, develop, and implement AI-enabled automation solutions for mining engineering and operational workflows.
• Work with mining specialists to identify high-value automation opportunities and convert technical requirements into practical digital solutions.
• Develop intelligent workflows that integrate geological, geotechnical, mine planning, operational, asset,
• Support the use of generative AI, machine learning, computer vision, and agent-based approaches to improve engineering productivity and decision support.
• Create reusable components and scalable solution patterns that can be applied across global mining projects.
• Develop automated pipelines to extract information from mining reports, PDFs, scanned documents, drawings, tables, figures, inspection records, and monitoring outputs.
• Apply OCR, layout understanding, multimodal models, and LLM-based techniques to identify entities, attributes, relationships, measurements, risks, and supporting evidence.
• Implement validation, normalization, exception-handling, and quality-control logic to improve the accuracy and consistency of extracted information.
• Maintain traceability between extracted outputs and the relevant source documents, pages, figures, tables, or evidence.
• Develop, validate, and support deployment of machine learning solutions for predictive analytics, anomaly detection, classification, risk assessment, optimization, and asset insights.
• Apply data science and statistical methods to identify patterns, trends, and actionable insights from engineering and operational data.
• Evaluate model performance, limitations, and suitability for mining use cases, working with domain experts to confirm engineering relevance.
• Contribute to proof-of-concept development and the transition of successful prototypes into maintainable production solutions.
• Support the design of structured knowledge models that connect mining assets, technical information, operational data, risks, controls, and engineering evidence.
• Contribute to knowledge graph and semantic data solutions using RDF, OWL, SPARQL, or equivalent technologies where appropriate.
• Develop graph-native and hybrid retrieval workflows, including GraphRAG approaches that combine structured graph context with AI models.
• Enable natural-language access to connected mining knowledge for engineering assistants, analytics tools, and decision-support applications.
• Support provenance, versioning, evidence linking, and auditability of AI-generated or graph-derived outputs.
• Develop and integrate solutions using Azure AI services, Azure OpenAI, Azure Machine Learning, Azure AI
• Build and maintain data pipelines, APIs, connectors, and services that integrate AI workflows with engineering platforms and enterprise data environments.
• Contribute to deployment, monitoring, documentation, testing, and continuous improvement of production AI applications.
• Support MLOps, prompt and model evaluation, access control, data security, and responsible AI practices.
• Work as part of the GCC Specialist Mining Services team to support multidisciplinary mining assignments delivered across WSP's global business.
• Collaborate with the Mining Automation Team Leader, mining engineers, geotechnical specialists, tailings
• Engage with project and domain teams to understand technical context, refine use cases, review outputs, and align solutions with project requirements.
• Communicate technical concepts clearly to both technical and non-technical stakeholders across different regions and time zones.
• Prepare solution .
• Knowledge Management and Graph-Based Intelligence