Senior Generative AI Lead (Azure)

Job Title: Senior Generative AI Lead (Azure)

Location:Jersey City,NJ

Candidates from NJ/NY preferred

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

• 12 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.