Lead AI/Agentic Architect

TEKsystems•Dallas, TX

3d•$85 - $90•Hybrid

About The Position

Our client is seeking an experienced Lead AI / Agentic Architect to provide strategic technical leadership for the design, implementation, and governance of enterprise-scale agentic AI solutions. This role will define the target architecture for next-generation AI agent platforms, lead the transition from Semantic Kernel to the Microsoft Agent Framework, establish governance and orchestration standards, and drive alignment across business, technology, and client stakeholders. The ideal candidate combines deep expertise in AI and distributed systems architecture with strong leadership capabilities and experience delivering solutions within highly regulated enterprise environments.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or related discipline.
10+ years of experience in enterprise architecture, software architecture, or technology leadership roles.
5+ years of experience designing AI, machine learning, or intelligent automation solutions.
Proven experience designing and delivering large-scale enterprise platforms and distributed systems.
Experience with Microsoft AI technologies, including: Microsoft Agent Framework, Semantic Kernel, Azure OpenAI Service, Azure AI Foundry, Azure AI Search, Microsoft Graph
Strong understanding of: Agentic AI architectures, Multi-agent orchestration, Retrieval-Augmented Generation (RAG), LLM integration patterns, Prompt and instruction orchestration
Expertise in cloud-native architecture and Azure services.
Excellent communication, presentation, and stakeholder management skills.

Nice To Haves

Experience within financial services or other highly regulated industries.
Experience implementing Responsible AI governance frameworks.
Knowledge of enterprise decisioning platforms and control-plane architectures.
Experience with AI observability, evaluation frameworks, and model governance.
Microsoft Azure certifications and/or AI certifications.
Experience leading large-scale digital transformation initiatives.

Responsibilities

Define and own the end-to-end architecture vision for enterprise agentic AI platforms.
Lead the transition from Semantic Kernel to the Microsoft Agent Framework and establish a scalable target-state architecture.
Design and document enterprise agent patterns, orchestration frameworks, communication protocols, and interaction models.
Establish standards for agent lifecycle management, memory, context handling, tool utilization, and multi-agent coordination.
Drive architectural decisions related to AI platform evolution, scalability, resiliency, and maintainability.
Design and implement governance, control-plane, and Decision OS integration strategies.
Define policies for agent authorization, monitoring, compliance, auditability, and human-in-the-loop controls.
Establish enterprise guardrails for responsible AI, security, risk management, and operational oversight.
Develop frameworks for agent observability, performance measurement, and operational governance.
Lead architecture and integration efforts across Midland and related enterprise platforms.
Design API, event-driven, and service-oriented integration patterns for AI-enabled business workflows.
Collaborate with engineering, platform, and business teams to ensure seamless integration across systems and data sources.
Provide technical guidance on cloud-native architecture, identity management, security, and infrastructure requirements.
Serve as the principal technical authority for agentic AI architecture decisions.
Lead architecture reviews, design sessions, and technical workshops with internal teams and client stakeholders.
Develop reference architectures, design standards, implementation frameworks, and best practices.
Mentor architects, engineers, and technical leads across AI-related initiatives.
Ensure architectural consistency and alignment across all workstreams.
Partner closely with PNC stakeholders to align architecture decisions with business objectives, governance requirements, and enterprise standards.
Communicate complex technical concepts to executive, business, and technical audiences.
Facilitate architecture alignment, risk assessment, and strategic planning discussions.
Support roadmap development and long-term AI transformation initiatives.