Engineer - AI (Mining Automation)

WSP seeks an Engineer - AI (Mining Automation) for its GCC Specialist Mining Services team in Noida or Mumbai, India. Reporting to the Mining Automation Team Leader, the engineer will build AI-enabled workflows that connect and analyze mining, asset, operational, geotechnical and technical information for engineering decisions on global projects. WSP describes a Hybrid Work Model.

Responsibilities

• Design reusable AI and automation solutions with mining specialists for mine planning, operations, tailings and water management, asset performance and risk management. Apply generative AI, machine learning, computer vision and agent-based approaches where suitable.
• Build pipelines that extract information from reports, PDFs, scans, drawings, tables, inspection records and monitoring outputs. Use OCR, layout understanding, multimodal models and LLM techniques; validate and normalize results while linking them to source evidence.
• Develop and evaluate models for prediction, anomaly detection, classification, risk assessment and optimization. Work with domain experts to assess engineering relevance and move successful prototypes toward maintainable production solutions.
• Develop structured knowledge models and graph-based or hybrid retrieval, including GraphRAG, to support natural-language access to mining information. Maintain provenance, versioning and auditability.
• Integrate AI workflows with engineering and enterprise systems through data pipelines, APIs and connectors, using Azure AI services where applicable. Support deployment, monitoring, testing, documentation, MLOps, model evaluation, access control, data security and responsible AI practices. Collaborate across disciplines and regions, prepare user guidance and contribute reusable team assets.

Qualifications

• Bachelor's or Master's degree in Mining Engineering, Computer Science, Data Science, Artificial Intelligence, Software Engineering, Geotechnical Engineering or a related discipline.
• Experience developing AI, machine learning, automation, analytics or document-intelligence solutions in mining, engineering, infrastructure, industrial or asset-intensive settings. Proficiency in Python and relevant AI or data-science frameworks; hands-on experience with LLMs, prompt engineering, retrieval-augmented generation or generative AI applications.
• Knowledge of data engineering, ETL or ELT, APIs, structured and unstructured data, and system integration; experience with OCR, document processing, computer vision, layout analysis or multimodal AI; and familiarity with Azure AI and data services. Employment is subject to successful background verification.