Lead Artificial Intelligence Engineer

Job Summary

We are hiring a Lead – GenAI + Dev Ops to architect and scale enterprise AI systems built on Azure. This role combines deep expertise in LLMs, Retrieval-Augmented Generation (RAG), vector search architecture, and cloud Dev Ops practices.

You will lead development of production-grade GenAI systems, design hybrid retrieval pipelines, and manage AI workloads in a secure Azure environment.

Key Responsibilities

Core AI Architecture

- Design RAG pipelines (chunking → embedding → retrieval → augmentation)
- Implement prompt engineering and LLM workflows
- Architect hybrid search systems (BM25 + vector + metadata filtering)
- Optimize semantic search relevance

Development

- Backend integration using Node.js
- Support AI-driven UI via React
- Manage conversation lifecycle logic
- Implement response analytics and feedback loops

Azure Infrastructure

- Azure Functions (event-driven serverless)
- Azure OpenAI & AI Search integration
- Cosmos DB / Postgre

SQL vector storage
- Azure SQL / MSSQL administration
- Identity management with Azure CLI credentials
- Logic Apps workflow automation

Dev Ops / AIOps

- CI/CD pipelines for AI apps
- Docker containerization
- Azure Dev Ops pipelines
- AI workload monitoring
- Security & encryption handling

Document & Data Systems

- Document ingestion pipelines
- File lifecycle tracking
- Privacy & encryption controls
- Analytics KPIs for AI systems

Required Skills

- LLM + Prompt Engineering expertise
- RAG architecture mastery
- Vector database systems (pgvector, HNSW)
- Azure OpenAI ecosystem experience
- Node.js backend engineering
- Dev Ops automation experience