AI Solution Architect
Location: Plano, TX (On-site)
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, productionready, scalable architectures aligned with governance standards.
Key Responsibilities
- Define reference architectures for LLM/RAG and multiagent 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 productionready 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 antipatterns 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.
Preferred
Experience with multiagent orchestration, enterprise integrations (ticketing, reporting, messaging), and regulated environments. Familiarity with governance processes and mixed DB landscapes.
Qualifications
8+ years in solution architecture; 3+ years in AI/LLM systems. Expertise in cloud platforms (Azure/AWS/Google Cloud Platform), 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.
Never miss an opportunity! Create an alert based on the job you applied for.