Enterprise AI Architect

System One, Inc.; Knoxville (TN); On-site; USD 150,000 - 230,000; Full time

Job summary

System One, Inc. is seeking an Enterprise AI Architect to provide technical leadership for AI initiatives in a regulated financial services environment. You will drive the architecture of Generative AI, Agentic AI, and multi-agent solutions from concept through production.

The role focuses on scalable AI patterns, secure enterprise integration, governance, and production readiness, with an emphasis on AWS-based environments. Strong collaboration with engineering and product teams is expected.

Qualifications

• 8+ years of enterprise architecture experience with Generative AI, Agentic AI, and production AI solutions.
• Hands-on knowledge of AI agents and multi-agent systems, including orchestration, memory, and retrieval.
• Strong experience with AWS and cloud-native technologies for scalable AI workloads.
• Experience integrating AI with enterprise APIs, applications, workflow systems, and data platforms.
• Knowledge of AI governance, Responsible AI, security, privacy, and regulatory compliance.
• Experience with retrieval-augmented generation, semantic search, and knowledge sources.
• Understanding production AI practices: evaluation, observability, monitoring, and lifecycle management.
• Knowledge of containers, IAM, API management, and enterprise integration patterns.
• Ability to communicate complex technical decisions to engineering, product, and executives.
• Prefer familiarity with Spec Driven Development (SDD) practices.

Responsibilities

• Lead enterprise architecture for Generative AI, Agentic AI, and multi-agent solutions.
• Define reusable AI architecture patterns, standards, reference architectures, and guidance.
• Establish patterns for AI agent orchestration, memory, retrieval, and human-in-the-loop workflows.
• Guide secure integration of AI with APIs, applications, workflows, identity services, and data sources.
• Incorporate security, privacy, governance, and auditability into AI solutions.
• Provide architecture leadership across multiple engineering and product teams.
• Conduct reviews, evaluate tradeoffs, and resolve complex implementation challenges.
• Support production AI capabilities: evaluation, observability, resiliency, and lifecycle management.
• Translate business objectives into AI technology roadmaps for technical and executive stakeholders.

Skills

Generative AI

Agentic AI

Production AI

AI governance

AWS cloud

Security & compliance

Architecture leadership

Multi-agent systems

Technical reviews

Reference architectures

Education

Bachelor's degree in Computer Science or Information Systems

Job description

Job Title

Enterprise AI Architect

Job Category

Architecture

Job Type

Permanent Full Time

Location

Lafayette, LA, Knoxville, TN, Columbia, SC, Birmingham, AL

Job Description

Enterprise AI Architect

Seeking an experienced Enterprise AI Architect to provide technical leadership for enterprise scale Artificial Intelligence initiatives within a highly regulated financial services environment. This role will lead the architecture of Generative AI, Agentic AI, and multi agent solutions from initial concept through production implementation.

The Enterprise AI Architect will establish scalable and reusable AI architecture patterns, guide engineering teams through key technical decisions, and ensure AI solutions integrate securely with enterprise platforms and cloud services. The role will have a strong focus on AWS based environments, enterprise integration, AI governance, security, Responsible AI, and production readiness.

This position is required in one of the following locations: Lafayette, LA, Knoxville, TN, Columbia, SC, Birmingham, AL.

Future Duties and Responsibilities

• Lead enterprise architecture for Generative AI, Agentic AI, and multi agent solutions.
• Define reusable AI architecture patterns, standards, reference architectures, and implementation guidance.
• Establish patterns for AI agent orchestration, tool integration, memory, retrieval, and human in the loop workflows.
• Guide secure integration of AI solutions with enterprise APIs, applications, workflow platforms, identity services, and data sources.
• Incorporate security, privacy, regulatory compliance, Responsible AI, auditability, guardrails, and human oversight into AI solutions.
• Provide architecture leadership and technical guidance across multiple engineering and product teams.
• Conduct architecture and technical reviews, evaluate tradeoffs, and help teams resolve complex implementation challenges.
• Support production AI capabilities including evaluation, observability, monitoring, resiliency, scalability, and model lifecycle management.
• Translate business objectives into AI technology roadmaps and communicate recommendations to technical and executive stakeholders.

Required Qualifications

• 8+ years of enterprise architecture experience with Generative AI, Agentic AI, and production AI solutions.
• Hands on knowledge of AI agents and multi agent systems, including orchestration, tool calling/integration, memory, retrieval, and human in the loop patterns.
• Strong experience with AWS and cloud native technologies used to deliver scalable enterprise applications and AI workloads.
• Experience integrating AI solutions with enterprise APIs, applications, workflow systems, identity services, and data platforms.
• Strong understanding of AI governance, Responsible AI, security, privacy, regulatory compliance, guardrails, and auditability, ideally within financial services or another highly regulated industry.
• Experience with RAG and enterprise knowledge retrieval, including semantic search, trusted knowledge sources, metadata, and data lineage concepts.
• Understanding of production AI practices, including evaluation, observability, monitoring, model lifecycle management, resiliency, and performance.
• Knowledge of containers, event driven systems, API management, IAM, and common enterprise integration patterns.
• Experience establishing architecture standards, conducting technical reviews, and providing implementation guidance across multiple engineering teams.
• Ability to create reference architectures and technology roadmaps and clearly communicate complex technical decisions to engineering, product, and executive stakeholders.
• Familiarity with AI assisted software development practices, requirements traceability, structured specifications, or Spec Driven Development (SDD) is preferred.

Educational Requirements

Bachelor's degree in Computer Science, Information Systems, or a related field.

Ref

#404-IT Pittsburgh