AI Solution Architect @ Plano, TX - EXT - Onsite

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.

• 8+ years in solution architecture; 3+ years in AI/LLM systems.
• Expertise in cloud platforms (Azure/AWS/GCP), Python, and AI frameworks (e.g., Lang Chain/Lang Graph, 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.

• 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; analyse 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 prioritise use cases and mentor engineering teams.

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