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.