AI Solution Architect

Location: Plano, TX (Onsite from Day 1)

Role Overview: Design and deliver agentic AI solutions, leveraging structured and unstructured data, applying RAG techniques and creating Action Agents for automation. Translate business needs into secure, production ready, scalable architectures aligned with governance standards.

Key Responsibilities: Define reference architectures for LLM/RAG and multi agent workflows. Develop solution architectures for structured and unstructured data using RAG; create Action Agents for task automation. Integrate heterogeneous data sources securely; ensure compliance and auditability. Build production ready solutions with CI/CD, IaC, observability, rollbacks, and SLOs; lead deployment across environments (dev/test/staging/prod).Quickly learn AT&T tools, frameworks, processes, and landscape; analyze use cases and identify optimal solutions. Apply best practices and avoid anti patterns in architecture, data integration, and AI workflows. Create solution design documents for each use case and develop proofs of concept (POCs) to validate feasibility. Partner with stakeholders to prioritize use cases and mentor engineering teams.

Qualifications: 8+ years in solution architecture; 3+ years in AI/LLM systems. Expertise in cloud platforms (Azure/AWS/GCP), Python, and AI frameworks (e.g., LangChain/LangGraph, vector databases).Strong knowledge of data engineering, security, governance, CI/CD, IaC (e.g., Terraform), and runtime observability (metrics, logs, tracing).Oracle OCI experience is a plus.

Preferred: Experience with multi agent orchestration, enterprise integrations (ticketing, reporting, messaging), and regulated environments. Familiarity with governance processes and mixed DB landscapes.