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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Product Owner - Engineering - **Company:** Diamondback E&P LLC - **Location:** Dallas, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Business Analytics Applications, Data Analysis, Information Systems, Python (Programming Language), Machine Learning, Operational Data Store, Performance Tuning, Software Product Management, Power BI, Snowflake, Functional Dependencies, Spotfire - **Published:** August 27, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18078040?backUrl=%2Fcareer%2F18078040%2FAi-Product-Owner-Engineering-Texas-Dallas ## About the Role * Bachelor's degree in Petroleum Engineering, Mechanical Engineering, Chemical Engineering, Industrial Engineering, Data Science, Information Systems, or a related technical field * 5+ years of experience supporting drilling, completions, production operations, marketing, or a closely related operational function within oil and gas * Experience leading cross-functional technology, analytics, process improvement, or business transformation initiatives in an operational environment * Experience translating operational workflows and business needs into clear requirements, priorities, and measurable outcomes * Experience working with operational, engineering, production, field, commercial, or analytics data and systems, including technologies such as Spotfire, WellView, Ignition, Snowflake, XSPOC, Python, Power BI, and similar platforms * Experience delivering or supporting AI, machine learning, automation, data, or analytics products from concept through adoption, * Direct Product Owner experience managing product roadmaps, backlogs, user stories, and acceptance criteria in an Agile environment * Experience using AI-enabled rapid product discovery techniques, including prototyping, user testing, workflow simulation, data exploration, or lightweight experimentation to test assumptions and reduce uncertainty before development. * Knowledge of AI model evaluation, operational data practices, responsible AI governance, model risk controls, and data quality requirements * Experience leading digital transformation or change adoption across Drilling, Completions, Production Operations, Marketing, or field operations teams * Familiarity with drilling performance optimization, completions execution, production surveillance, artificial lift optimization, production forecasting, operational reporting, and field data management workflows ## Description The AI Product Owner - Engineering serves as the primary business representative for Artificial Intelligence (AI) products supporting Diamondback Energy's Drilling, Completions, Production Operations, Marketing, and related field operations workflows. This role owns the product outcome lifecycle from opportunity identification and discovery through prioritization, product definition, business validation, adoption, value realization, and continuous improvement. The Product Owner partners with AI Engineering & Delivery and other technology teams for technical feasibility, solution engineering, productionization, deployment, and technical operations. The Product Owner combines operational domain knowledge, product ownership skills, and AI fluency to deliver responsible solutions that improve operational efficiency, production optimization, field execution, commercial performance, and operational decision-making across the asset lifecycle., Include but are not limited to * Partner with Drilling, Completions, Production Operations, Marketing, and related stakeholders to understand workflows, user needs, data requirements, controls, and operational challenges, and identify, evaluate, and prioritize AI and automation opportunities based on business value, technical feasibility, risk, data readiness, and strategic alignment. * Own the business problem definition, product vision, target users and workflows, value hypothesis, roadmap, priorities, success measures, and expected business outcomes, partnering with business sponsors and the AI Value & Economics Lead to establish baseline performance and the approach for measuring realized outcomes before significant investment. * Lead product discovery to validate the business problem, user needs, workflows, constraints, value hypothesis, and potential solution approaches before significant production investment, using rapid prototypes, workflow simulations, data exploration, user testing, vendor capability assessment, and other lightweight experiments to reduce uncertainty and test assumptions. * Translate business needs into clear product requirements, user stories, success criteria, acceptance criteria, and AI quality expectations. * Manage the product backlog and make product scope and priority decisions; lead business validation and user acceptance testing; and hold product acceptance decision rights against defined requirements, acceptance criteria, user needs, and expected business outcomes. * Partner with technology, data, security, governance, legal, risk, and operational subject matter experts to deliver scalable solutions that meet responsible AI, confidentiality, data quality, and compliance requirements. * Represent Drilling, Completions, Production Operations, and Marketing stakeholder needs; coordinate cross-functional dependencies with Geoscience, Reservoir Engineering, Finance, and other business functions; and support user readiness and adoption. * Own post-launch product performance and continuous improvement by monitoring adoption, AI performance, business outcomes, realized value, user feedback, and relevant risk measures, and prioritize the changes needed to improve product outcomes. ## Related Videos - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) - [How Cisco embraced a DevOps culture within its network engineering team](https://www.wearedevelopers.com/videos/99-how-cisco-embraced-a-devops-culture-within-its-network-engineering-team) - [Inside Look: AI & Developer Productivity Programs in a 1,500+ Engineering Team](https://www.wearedevelopers.com/videos/100260-inside-look-ai-developer-productivity-programs-in-a-1-500-engineering-team) - [REST, GraphQL, gRPC, and more: A comparison of modern API styles](https://www.wearedevelopers.com/videos/100247-rest-graphql-grpc-and-more-a-comparison-of-modern-api-styles) - [Hacking AI at the Edge of the Indian Ocean](https://www.wearedevelopers.com/videos/100177-hacking-ai-at-the-edge-of-the-indian-ocean) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)