AI Embedment Lead

Overview

In this role you will lead the embedding of AI-driven solutions in Shell’s upstream assets to deliver measurable operational and financial value. You work with cross-functional teams to translate business challenges into AI opportunities, ensuring solutions fit real subsurface and production workflows. You’ll develop and deploy generative and agentic AI, driving adoption and repeatable value across assets. This is a high-autonomy role focused on fast execution, impact, and scalable, production-ready outcomes.

Pay / Benefits

• flexible working hours
• remote/mobile working
• competitive starting salary
• paid parental leave
• training and development programmes
• diverse and inclusive culture

Responsibilities

• Partner with asset leadership and operations teams to identify AI-enabled value opportunities
• Prioritize use cases with clear operational or economic impact using subsurface and wells domain knowledge
• Translate ambiguous business challenges into actionable AI solutions
• Act as translator between innovation teams and business stakeholders
• Ensure AI solutions reflect real workflows and data realities (uncertainty, quality, decision cycles)
• Lead implementation of generative AI solutions, agentic AI systems, and advanced analytics
• Collaborate with data scientists, engineers, and platform teams to deploy robust solutions
• Drive adoption through training, change management, and iterative refinement
• Ensure solutions are scalable, reliable, and user-centric
• Identify reusable components and contribute to reusable frameworks and best practices
• Share learnings to accelerate adoption and value capture
• Adhere to data governance, security, and responsible AI standards
• Validate outputs with appropriate human oversight during decision-making

Key requirements

• Bachelor's degree
• Deep expertise in petrophysics/formation evaluation or production engineering/production technology
• Proven experience developing or deploying Agentic AI and GenAI solutions
• Strong Python and AI/ML solution development skills
• Hands-on experience building LLM applications and agentic systems
• Regular use of AI coding assistants and agents
• Experience with data analytics and visualization tools (Databricks, Plotly Dash, Spotfire)
• Knowledge of data pipelines, solution architecture, and deployment best practices
• Experience delivering production-ready solutions
• Design-thinking mindset and track record of technology innovation and adoption
• Excellent communication and cross-functional collaboration skills

• communication
• collaboration
• relationship-building
• Python
• AI/ML development
• Generative AI (GenAI)

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