AI & Integration Architect

Permian Resources•Midland, TX

3d•Onsite

About The Position

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 company's 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.

Requirements

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.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Nice To Haves

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

Responsibilities

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 company's 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.
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.