GenAI Solution Architect - Azure AI / LLM & Agentic Systems
Role Description:
This role requires an experienced Solution Architect specializing in GenAI, LLM orchestration, NLP, and Azure AI ecosystems. The architect will design scalable AI platforms, define reusable reference architectures, and guide engineering teams in building enterprise‑grade AI systems aligned with BFSI security and governance standards.
Core Responsibilities:
End‑to‑End GenAI Architecture
Design scalable AI/GenAI solutions on Azure using AI Foundry, Azure OpenAI, and Azure AI Search
Define architecture patterns for retrieval, orchestration, grounding, and secure deployment
Agentic & Multi‑Agent System Design:
Architect advanced AI systems using LangChain / LangGraph
Enable tool‑calling, routing, memory, and stateful workflows
Reference Architecture Definition
Create reusable architectures for:
RAG
Conversational AI
Document processing
Copilots
Decision‑support systems
LLM Orchestration Frameworks
Govern implementation of chains, retrievers, tools, and graph‑based workflows
Establish best practices for modular orchestration
Advanced Workflow Patterns:
Define patterns such as:
Supervisor–worker models
Branching logic
Human‑in‑the‑loop interactions
Prompt Engineering & Evaluation
Standardize prompt design, versioning, testing, and regression
Establish observability practices (logs, traces, metrics)
NLP & Language AI Leadership:
Lead NLP solution design for:
Classification
Summarization
Semantic search
Entity extraction
Leverage Azure AI Language
Python & AI Engineering Standards:
Guide API/microservices architecture
Enforce coding standards and lifecycle management
Optimize performance and cost
Enterprise Security & Governance:
Ensure compliance with BFSI standards using:
Entra ID
RBAC
VNET
Private endpoints
Responsible AI practices
Stakeholder Engagement & Pre‑Sales:
Lead workshops and architecture discussions
Translate business needs into architecture decisions (ADRs)
Support RFPs, proposals, and clien:t solutioning