Sr Lead Architect

Area(s) of responsibility
Key Job Responsibilities
Architecture & Design
Define end-to-end AI/GenAI architecture for enterprise applications
Design scalable solutions using LLMs, RAG pipelines, vector databases, and agentic workflows
Azure AI Platform
Architect solutions using Azure OpenAI, Azure ML, Databricks, AI Search
Design cloud-native architectures (scalability, HA/DR, cost optimization)
Development & Engineering
Lead hands-on Python development for AI/ML and GenAI applications
Build APIs, microservices, and reusable AI components
GenAI Implementation
Implement:
RAG (retrieval-augmented generation) pipelines
Vector search and embeddings
Multi-agent and tool-calling frameworks
Develop AI copilots, chatbots, and automation systems
Governance & Security
Ensure Responsible AI, compliance, and data governance (PII, lineage, security)
Implement guardrails: prompt security, content filters
Leadership & Collaboration
Provide architecture guidance and mentor engineering teams
Work with business stakeholders to translate requirements into solutions
Mandatory Skills
AI/ML & GenAI
LLMs (GPT or open-source), RAG, embeddings, vector databases
Experience building enterprise GenAI solutions
LangChain, LangGraph
Agentic AI
Programming
Strong expertise in Python (mandatory)
Experience with APIs, microservices
Azure Cloud
Hands-on with:
Azure OpenAI / AI Studio
Azure ML, Databricks, Synapse
Storage (Blob, Cosmos DB), AI Search
Architecture
Experience designing scalable, distributed systems
Strong knowledge of cloud-native architecture patterns
Experience
10+ years in IT
5+ years in AI/ML
2+ years in Generative AI / LLM-based systems
Preferred Skills
Experience with:
LlamaIndex, Autogen, CrewAI
Multi-agent systems
Exposure to:
Vector DBs
Data platforms
Cloud & Platform:
Multi-cloud (AWS/GCP)
Kubernetes, containers
Governance:
Data governance tools (Purview, cataloging, lineage)
Certifications:
Azure Solutions Architect / Azure AI Engineer

Work arrangement
No