AI Architect Atlanta - GA - Georgia

Example: PTN_US_9999999_SKIPJOHNSON0413

Experience Required: 12+ Years

Position Overview

We are seeking an experienced AI Architect to lead the architecture, governance, and strategic implementation of an AI-enabled Quality Engineering Center of Excellence. The candidate will define the target architecture for AI agents, multi-agent orchestration, Retrieval-Augmented Generation (RAG), and enterprise AI adoption across the software development lifecycle. This is a customer-facing onsite role requiring strong AI architecture, engineering, governance, and stakeholder-management capabilities.

Key Responsibilities

AI Architecture Leadership: Define the enterprise architecture, reference patterns, and technology roadmap for AI-powered Quality Engineering solutions.

Agentic AI and RAG: Design reusable AI-agent patterns and a RAG Knowledge Fabric integrating Jira, Confluence, Git repositories, CICD platforms, test assets, ServiceNow, and approved enterprise data sources.

Orchestration and Integration: Design multi-agent orchestration and integration services supporting requirements review, code quality, test preparation, test execution, QE intelligence, and release assurance.

Governance and Responsible AI: Establish Human-in-the-Loop controls, security guardrails, explainability, confidence scoring, model evaluation, observability, auditability, and cost controls.

Stakeholder and Technical Leadership: Lead architecture reviews, prioritize high-value use cases, guide onsite and offshore teams, and communicate solution decisions to business and engineering leadership.

Scale and Adoption: Define the maturity path from supervised to semi-autonomous and autonomous agents while ensuring scalability, reliability, performance, and adoption.

Required Qualifications

12+ years of technology experience, including 5+ years in AIML, Generative AI, or intelligent automation.

Strong experience with LLM applications, Agentic AI, multi-agent systems, RAG, embeddings, vector search, prompt engineering, and AI evaluation.

Experience with enterprise AI architecture, microservices, APIs, event-driven architecture, containers, and cloud-native deployment.

Hands-on knowledge of Claude, Gemini, Codex, Azure OpenAI, or equivalent enterprise LLM platforms.

Proficiency in Python and working knowledge of Java andor TypeScript, REST APIs, FastAPI, Git, CICD, Docker, and Kubernetes.

Strong knowledge of responsible AI, security, privacy, model-risk controls, monitoring, and production-support practices.

Strong customer-facing communication, architecture presentation, and cross-functional leadership skills.

Preferred Qualifications

Bachelor s or Master s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Experience in Retail, Supply Chain, Logistics, Distribution, or a related business domain.

Relevant AI, cloud, architecture, software engineering, or Quality Engineering certifications.

Key Skills

Generative AI, Agentic AI, Multi-Agent Architecture, RAG, Knowledge Fabric, Vector Search, Prompt Engineering, AI Evaluation, Responsible AI, Python, FastAPI, APIs, Microservices, Docker, Kubernetes, CICD, Jira, Confluence, GitHubGitLab, Azure DevOps, ServiceNow.

Success Measures

Approved and scalable AI-CoE architecture successful rollout of RAG and orchestrated AI agents improved QE productivity and automation coverage measurable accuracy, reliability, adoption, security, and API-cost controls reusable standards across applications and programs.

Ideal Candidate

A senior AI architect who combines hands-on technical depth with enterprise architecture and customer-facing leadership. The candidate should be able to convert the AI-CoE vision into secure, scalable, and practical solutions while guiding teams through adoption.

Skills: Generative AI - Quality Engineering

Experience Required: 12 & Above