GEN AI Architect

Role & responsibilities

Generative AI Architect

Key Responsibilities

1. Solution Architecture & Design

• Design and architect

  Generative AI-based Knowledge Mining systems

  using Azure OpenAI, Cognitive Search, and vector databases.
• Define

  end-to-end RAG (Retrieval-Augmented Generation)

  pipelines for intelligent document querying and contextual answering.
• Architect

  document validation

  workflows using

  Azure Document Intelligence (Form Recognizer)

  for structured and unstructured data extraction.
• Design

  contract validation pipelines

  to extract obligations, risks, clauses, and compliance information from legal documents.
• Ensure

  system scalability

  through distributed processing and asynchronous workflows using Azure Functions, Service Bus, and Event Grid.
• Build and integrate

  LLM-based reasoning systems

  for document verification, summarization, and anomaly detection.

2. Governance, Performance, and Security

• Define

  governance models

  for data privacy, ethical AI, and secure prompt management.
• Optimize system latency, throughput, and token efficiency for real-time or near-real-time processing.
• Implement

  RBAC (Role-Based Access Control)

  and API management using Azure AD, API Management, and Managed Identities.
• Expertise in Feedback loops & Models Evaluations

Architectural Skills

• Expertise in

  microservices and serverless architectures

  .
• Experience designing

  high-availability, scalable AI systems

  .
• Familiarity with

  observability, monitoring, and telemetry

  in Azure (App Insights, Log Analytics).
• Strong understanding of

  data pipelines and ETL frameworks

  (ADF, Synapse, or custom Python).