AI Engineer

Permian Resources; Midland (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Permian Resources (NYSE: PR) is seeking an AI Engineer in Midland, TX reporting to the Head of AI. This is a hands-on leadership role: from day one, you will architect and deliver production AI systems while shaping how the AI function grows over time.

Responsibilities include owning the full lifecycle of models and agents in production, guiding build-versus-buy decisions, and partnering with the data engineering team to modernize the data platform across Azure Databricks and related data

Qualifications

• Hands-on experience building AI and data applications into production.
• Ability to lead a technical team and manage groups of varying size.
• Experience deploying models and AI agents including validation and monitoring.

Responsibilities

• Own architecture and delivery of production AI systems.
• Define and shape the AI function's growth and roles.
• Build or lead a small high-leverage team over time.
• Extend influence across the organization with a hub-and-spoke model.
• Own full lifecycle of models and agents in production.

Skills

Hands-on AI

Technical leadership

Production ML lifecycle

Azure Databricks

Architecture & delivery

Education

Bachelor's degree in CS/Math/Engineering

Tools

Azure Databricks

Job description

Job Description:

Permian Resources (NYSE: PR) is currently seeking an AI Engineer in Midland, TX reporting to the Head of AI. This is a hands-on leadership role: from day one, the AI Engineer architects and delivers production AI systems directly, while also shaping how the company's AI function grows and operates over time.

General Responsibilities

• Own hands-on architecture and delivery of production AI systems from day one, with full platform access across the company's AI and data environment.
• Define and shape the AI function's next roles, starting with a Knowledge Engineer who owns ontology control and a future ML Engineer who owns MLOps and monitoring for AI models and agents, rather than inheriting fixed job descriptions.
• Build and lead a small, high-leverage team over time, or operate with broad authority across a team built around the role: the growth path is intentionally flexible and shaped by the person in it.
• Extend influence beyond direct reports through a hub-and-spoke model, setting how AI systems integrate, operate, and improve across the broader organization.
• Own the full lifecycle of models and agents in production, from methodology selection through validation, orchestration, safety controls, and ongoing performance monitoring.
• Shape the company's build-versus-buy strategy for AI: a mix today that shifts toward in-house build over time, with partners where it makes sense, and with anything currently sourced externally subject to future review for whether it should be built in-house instead.
• Contribute to a shared data and AI layer strategy: an integrated system that gives the company a single, connected way to act on its data, built on top of its existing Azure Databricks foundation.
• Retain decision authority over AI work executed by outside consultants or systems integrators, so the company directs the work rather than simply receiving it.
• Partner closely with the company's data engineering team as it modernizes its data platform, moving from static tables toward real-time data products, providing requirements and design input without owning that team's pipelines.

Required Qualifications

• Proven, hands‑on experience building AI and data applications from the ground up and taking them into production, not just prototyping.
• Demonstrated ability to evaluate and adopt new AI technologies and platforms as the field evolves, translating them into working systems.
• Comfort operating as a hands‑on technical lead while also leading and developing a team, with experience managing groups ranging from a handful of people to a dozen or more.
• Working knowledge of the full lifecycle of deploying models and AI agents into production, including validation, orchestration, safety controls, and performance monitoring.
• Experience working with cloud data platforms such as Databricks and unifying data from multiple operational sources for use in AI systems.
• Bachelor's degree in computer science, data science, engineering, or a related field, or equivalent practical experience.

Preferred Qualifications

• Experience delivering high‑value AI use cases within the Oil & Gas industry.
• Experience building the business case for AI investments, including articulating expected value and return to non‑technical executive stakeholders.
• Experience establishing responsible‑AI practices, including documentation standards, human oversight, and monitoring and guardrails for models and agents running in production.
• Experience standing up or scaling a technical function from a small team into a larger one over time.
• Domain exposure to upstream oil and gas or another asset‑intensive, industrial sector, or comparable comfort operating in a highly regulated, data‑rich physical‑operations environment.

Permian Resource is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.