Title:  Well Integrity Services Leader

Main Responsibilities

• Design, develop, test, deploy, and support software applications used in well construction operations.
• Develop full-stack solutions, including user interfaces, APIs, databases, integrations, and cloud-based services.
• Develop machine learning models, AI agents, workflow automation solutions, and advanced analytics applications.
• Deploy and maintain physics-based models, numerical simulations, and engineering calculation engines.
• Implement DevOps, CI/CD, monitoring, and observability practices to ensure reliable software delivery and operation.
• Collaborate with engineers and business stakeholders to define requirements and translate operational needs into software solutions.
• Validate software, models, and analytical tools using field data, testing, and user feedback.
• Troubleshoot production issues, optimize system performance, and support software deployments.
• Contribute to technical documentation, code reviews, architecture decisions, and software development standards.
• Evaluate emerging technologies and identify opportunities to improve products, workflows, and engineering capabilities.

Experience

• Hands-on experience in software engineering, cloud-native application development, and digital product delivery.
• Active involvement in coding, testing, deployment, architecture, and operational support of engineering software, APIs, databases, integrations, and cloud services.
• Experience developing machine learning models, AI agents, workflow automation, and decision-support systems.
• Experience in scientific computing, physics-based modeling, simulation tools, engineering algorithms, predictive models, and AI-enabled solutions.
• Experience transforming operational challenges into scalable digital products and decision-support tools.

Knowledge

• Software engineering and cloud-native application development.
• Engineering software, APIs, databases, integrations, and cloud services.
• Scientific computing and physics-based modeling.
• Simulation tools, engineering algorithms, and predictive models.
• Machine learning, artificial intelligence, AI agents, workflow automation, and decision-support systems.
• Data analytics and advanced analytical applications.
• DevOps, CI/CD, monitoring, and observability practices.
• Software architecture and digital product development.

Skills

• Ability to transform operational challenges into scalable digital products and decision-support tools.
• Strong collaboration skills to work effectively with engineers, developers, and business stakeholders.
• Innovation mindset to identify opportunities, prototype new ideas, evaluate emerging technologies, and transform concepts into production-ready solutions.
• Analytical skills to validate software, models, and analytical tools using field data, testing, and user feedback.
• Problem-solving skills to troubleshoot production issues and optimize system performance.
• Ability to contribute to technical documentation, code reviews, architecture decisions, and software development standards.