About the role
Role Overview
We are seeking a highly experienced Generative AI Architect with deep expertise in designing and deploying enterprise-scale AI solutions using Microsoft Azure. The ideal candidate brings strong experience in LLMs, agentic AI, and advanced data science, with a proven track record of delivering production-grade AI systems across industries such as banking, healthcare, and enterprise SaaS.
Key Responsibilities
- Generative AI Solution Architecture
Design and implement end-to-end GenAI systems leveraging Azure OpenAI Service and modern LLMs (e.g., GPT-4o) - Architect scalable RAG (Retrieval-Augmented Generation) pipelines with vector databases and semantic search
- Build and orchestrate multi-agent systems using frameworks like LangChain, LangGraph, and CrewAI
- Define system architecture including APIs, microservices, and cloud-native deployments
- Azure AI & Cloud Implementation
Develop AI solutions using: Azure AI Studio / Azure AI Foundry Azure Cognitive Services - Deploy secure, scalable applications on Azure (App Services, containers, serverless)
- Integrate AI workflows with enterprise platforms such as Microsoft Teams and Copilot Studio
- Advanced AI Engineering
Implement prompt engineering, fine-tuning (LoRA, QLoRA, DoRA), and model optimization techniques - Develop intelligent systems for:
Document processing (PDFs, images, structured/unstructured data)
Semantic search and information retrieval
Automated reasoning and decisioning systems
Apply evaluation frameworks (RAGAS, LLM-as-Judge) for model performance and reliability - Data Engineering & Integration
Design data pipelines and ingestion frameworks using Azure Data Factory and enterprise data sources
Implement vector search using PostgreSQL (pgvector), ChromaDB, or Azure-based solutions
Optimize retrieval using embeddings, cosine similarity, reranking, and top-k strategies - MLOps, Deployment & Observability
Build and manage CI/CD pipelines for AI systems using Azure Machine Learning
Ensure system observability, monitoring, and performance tuning
Implement secure deployment practices, environment isolation, and governance - Leadership & Collaboration
Lead cross-functional teams of data scientists, engineers, and product managers
Provide architectural guidance and technical mentorship
Translate business requirements into AI-driven solutions aligned with compliance and regulatory standards
Drive innovation initiatives and enterprise AI adoption
Required Qualifications
Experience
15+ years in software engineering with 8+ years in AI/ML
Proven experience delivering production-grade GenAI systems
Strong background in enterprise architecture and technical leadership
Technical Skills
Expertise in Microsoft Azure ecosystem
Strong proficiency in Python, FastAPI, and RESTful services
Deep knowledge of:
LLMs, embeddings, and vector databases
RAG architecture and agentic AI systems
NLP models (BERT, RoBERTa, ALBERT)
Experience with tools/frameworks:
LangChain, LangGraph, CrewAI
Hugging Face, PyTorch, TensorFlow
Streamlit, Docker, Kubernetes
Preferred Qualifications
Certifications in Azure AI (e.g., Azure AI Engineer, Azure AI Fundamentals)
Experience with Copilot Studio and enterprise AI assistants
Exposure to multi-cloud environments (AWS SageMaker, etc.)
Strong understanding of Responsible AI and governance.
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