Description

Design and deliver production-ready agentic AI solutions using structured and unstructured data. Define reference architectures for LLM/RAG and multi-agent workflows, creating Action Agents for automation. Integrate heterogeneous data sources securely while ensuring compliance, auditability, and governance standards.

Responsibilities

• Define reference architectures for LLM, RAG, and multi-agent workflows.
• Develop solution architectures for structured and unstructured data using RAG and Action Agents.
• Build production-ready solutions with CI/CD, IaC, observability, rollbacks, and SLOs.
• Lead deployment across dev, test, staging, and prod environments.
• Create solution design documents and POCs to validate feasibility and prioritize use cases.

Required Skills

• 8+ years in solution architecture; 3+ years in AI/LLM systems.
• Expertise in cloud platforms: Azure, AWS, or GCP.
• Proficiency in Python and AI frameworks (LangChain, LangGraph).
• Strong knowledge of vector databases and data engineering.
• Experience with CI/CD pipelines and IaC (e.g., Terraform).
• Knowledge of runtime observability (metrics, logs, tracing).
• Understanding of security, governance, and compliance standards.

Preferred Skills

• Experience with multi-agent orchestration and enterprise integrations (ticketing, reporting, messaging).
• Familiarity with regulated environments and mixed database landscapes.
• Oracle OCI experience.

Key Skills

Education

Any Graduate