AI & Integration Architect

Job Description:

Permian Resources (NYSE: PR) is seeking an AI & Integration Architect in Midland TX. This role owns the application orchestration and AI-collaboration layers of Permian Resources enterprise AI platform and is accountable for how AI applications and agents are built governed deployed and connected across the business. This is a founding platform role: the incumbent stands up the companys AI Agent Center of Excellence sets the enterprise standards and reference architectures that delivery teams build within and serves as the senior technical decision partner to the Head of AI. It blends hands-on architectural authority with enterprise scope owning the platform the operating model governance and safety and the multi-year roadmap for agentic AI.

General Responsibilities

Leadership & Scope

Own the enterprise AI application orchestration and integration platform and its multi-year roadmap; be accountable for platform outcomes adoption cost and risk.

Stand up the AI Agent Center of Excellence: the operating model standards reusable patterns enablement and use-case intake and prioritization.

Set the enterprise reference architectures guardrails and shared model catalog that AI delivery teams build within; act as the design authority for agentic AI.

Build mentor and technically lead a team of AI and integration engineers (direct and matrixed); grow the companys agentic-AI talent bench.

Serve as the senior technical decision partner to the Head of AI; own build-versus-partner-versus-buy and platform-investment recommendations.

Chair the AI architecture and governance review; be accountable for enterprise AI risk model and agent safety and regulatory compliance.

Represent the AI platform to executive leadership and to risk audit and security stakeholders; translate platform strategy into board-ready investment decisions.

Core Platform Responsibilities

Own and govern Microsoft Foundry (Azure AI Foundry) as the enterprise orchestration platform for building deploying evaluating and governing AI applications and agents setting standards for project structure environments and the shared model catalog and delegating delivery to the teams that build within them.

Architect and lead the enterprise AI agent program: how agents are designed orchestrated (single- and multi-agent) granted tools given memory and context evaluated and promoted to production and codify the reusable pattern library the organization adopts.

Own model strategy at the orchestration layer: model catalog and selection routing across providers and tiers prompt and tool-use patterns and a model-agnostic posture so the company is never locked to a single vendor.

Define and govern the integration surface between AI applications/agents and the data platforms knowledge services and systems of record they depend on via clean versioned APIs and contracts.

Establish enterprise LLMOps/AgentOps practices as company standards: evaluation harnesses observability and tracing prompt and version management regression testing drift detection retraining triggers and rollback procedures.

Own governance security and identity integration for AI applications and agents: authentication authorization data-access boundaries content-safety guardrails and audit trails; be accountable for the controls that support SEC and energy-sector regulatory compliance.

Lead build-versus-partner-versus-buy strategy with the Head of AI and own platform tooling and vendor investment recommendations at the application and orchestration layers.

Lead cross-functional delivery turning prioritized use cases and knowledge-graph services into governed orchestrated production AI applications by directing data security platform and business partners.

Required Qualifications

12 years in senior AI/solution architecture including ownership of enterprise application and orchestration layers (not just models or notebooks) and delivery of AI/ML applications to production.

Hands-on and strategic ownership of Microsoft Foundry / Azure AI Foundry or strong directly transferable experience with a comparable enterprise AI orchestration platform.

Track record designing and shipping LLM-powered applications and multi-agent systems: orchestration tool/function calling retrieval memory and structured output.

Experience with GenAI orchestration frameworks (e.g. LangChain LlamaIndex Semantic Kernel or comparable) and retrieval-augmented generation (RAG)/vector-store integration patterns.

Deep Microsoft Azure ecosystem fluency: identity (Entra ID) networking security and container/app hosting including enterprise landing-zone design.

Enterprise LLMOps/MLOps discipline: evaluation observability versioning and safety/quality gating for AI systems.

Demonstrated leadership beyond individual delivery: mentoring engineers setting technical standards others adopt and advising executive/C-suite stakeholders.

TOGAF (or equivalent) enterprise-architecture grounding and/or an advanced degree in AI/ML.

Bachelors degree in Computer Science Engineering or a related field or equivalent practical experience.

Preferred Qualifications

Experience standing up an enterprise AI agent platform or Center of Excellence from the ground up establishing the operating model standards and governance others adopt.

Multi-cloud AI platform fluency (AWS Azure and/or Google Cloud) reflecting a provider-agnostic approach.

Experience building audit trails and compliance controls for agentic or automated workflows in a regulated environment.

Familiarity with multi-agent orchestration frameworks and emerging agent-interoperability standards (e.g. MCP A2A).

Oil & gas domain experience or experience in another complex regulated operating environment.

Masters degree in Artificial Intelligence / Machine Learning or a closely related discipline; expert-level Azure certifications; recognized community/thought leadership in the Azure/AI ecosystem.

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