Required skills:
• • 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.
• pply 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.

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