AI Architect

Company Overview  

10Pearls is an end-to-end digital technology services partner helping businesses utilize technology as a competitive advantage. We help our customers digitalize their existing business, build innovative new products, and augment their existing teams with high-performance team members. Our broad expertise in product management, user experience/design, cloud architecture, software development, data insights and intelligence, cybersecurity, emerging tech, and quality assurance ensures that we are delivering solutions that address business needs. 10Pearls is proud to have a diverse clientele including large enterprises, SMBs, and high-growth startups. We work with clients across industries, including healthcare/life sciences, education, energy, communications/media, financial services, and hi-tech. Our many long-term, successful partnerships are built upon trust, integrity, and successful delivery and execution.   

Role  

As an AI Architect in the oil and gas sector, you will design, implement, and oversee AI systems that enhance operational efficiency, optimize production, and drive innovation. Your role focuses on defining the architecture for AI and machine learning solutions, ensuring scalability, reliability, and alignment with business objectives. 

Responsibilities 

• Define the AI strategy and architecture to address business needs across exploration, production, and operational domains. 

• Develop roadmaps for integrating AI into existing systems, focusing on scalability and long-term sustainability. 

• Identify and prioritize AI use cases, such as predictive maintenance, reservoir modelling, and supply chain optimization. 

• Design end-to-end architectures for machine learning pipelines, including data ingestion, model development, training, and deployment. 

• Implement MLOps best practices for continuous integration, deployment, and monitoring of AI models. 

• Implement AI explainability frameworks such as SHAP, LIME, and Explainable AI (XAI) to enhance transparency. 

• Develop human-in-the-loop (HITL) AI systems for critical decision support in exploration and production. 

• Design AI models with bias detection and fairness auditing mechanisms. 

• Automate cloud-based AI model provisioning using infrastructure as code (IaC) principles. 

• Select appropriate frameworks, libraries, and tools (e.g., TensorFlow, PyTorch, Scikit-learn) for AI development. 

• Build scalable solutions using cloud platforms like AWS, Azure, or Google Cloud, leveraging tools such as Kubernetes and Docker for containerization. 

• Establish data standards, pipelines, and governance policies to ensure high-quality input for AI models. 

• Implement monitoring systems to track performance, retrain models as necessary, and maintain accuracy over time. 

• Develop strategies to address bias, fairness, and ethical considerations in AI systems. 

• Design AI solutions that integrate seamlessly with existing oil and gas technologies, such as SCADA systems, IoT sensors, and geophysical modelling tools. 

• Develop AI models tailored to specific oil and gas applications, such as seismic data analysis, drilling optimisation, and production forecasting. 

• Enable real-time analytics and decision support through edge computing and AI-enabled IoT systems. 

• Stay current with the latest advancements in AI and recommend technologies that align with business objectives. 

• Collaborate with data scientists, engineers, and business leaders to align technical solutions with operational goals. 

• Guide teams in best practices for AI development, deployment, and maintenance. 

• Ensure all AI systems comply with industry regulations and data privacy standards. 

• Implement robust cybersecurity measures to protect sensitive data and AI systems from threats. 

• Document architectures, workflows, and operational guidelines for transparency and compliance audits. 

Requirements 

• Knowledge of deep learning, natural language processing, computer vision, and reinforcement learning techniques. 

• Expertise in AWS, Azure, or Google Cloud for deploying AI solutions. 

• Strong ability to work with multidisciplinary teams, including engineers, data scientists, and business stakeholders. 

• Excellent ability to translate complex technical concepts into actionable business strategies. 

• Design AI solutions to reduce downtime, optimise drilling accuracy, and improve production yields. 

• Leverage tools such as Kubeflow, MLflow, and SageMaker Pipelines for end-to-end ML lifecycle management. 

• Implement predictive analytics to prevent equipment failures and optimise resource allocation. 

• Enable advanced applications like digital twins, automated geophysical analysis, and AI-driven reservoir modelling. 

• Familiarity with data processing frameworks (e.g., Apache Spark, Hadoop). 

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred). 

• 8+ years of experience in AI/ML development, with at least 3 years in an architecture or leadership role. 

• Strong understanding of oil and gas industry workflows and challenges. 

• Expertise in AI/ML frameworks and big data technologies. 

• Practical experience with a statistical programming language (e.g., Python, R) and applied machine learning techniques for AI model development.