Agile Architect (W2 only)

Job Title: Agile Architect (W2 only)
Location: Atlanta, GA (Onsite)
Experience: 12+ years

Skills: Generative AI - Quality Engineering

Job Description:
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, CI/CD 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 AI/ML, 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 and/or TypeScript, REST APIs, FastAPI, Git, CI/CD, 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, CI/CD, Jira, Confluence, GitHub/GitLab, 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.