Job Title: Senior Generative AI Architect (Azure)
Location:Remote
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
1. 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
2. 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
3. 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
4. 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
5. 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
6. 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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