Job Description

Freelancing Opportunity

: Azure AI RAG EngineerRole Overview

We are seeking an experienced

Azure AI RAG Engineer

to design, develop, and deploy advanced Retrieval-Augmented Generation (RAG) systems using Azure AI services. The ideal candidate will excel in building scalable semantic search pipelines, containerized AI applications, and secure, production-grade microservices.

Core Responsibilities

Architect and implement

RAG pipelines

using Azure AI Search, OpenAI embeddings, and custom reranking logic. Develop and deploy

containerized AI applications

using Docker and Azure Container Apps. Build

semantic search systems

with hybrid retrieval, chunking, enrichment, and vector indexing. Integrate NLP workflows for

document ingestion, summarization, and entity extraction

via Azure AI Language and Azure Document Intelligence. Implement

reranking models

using transformer-based scoring and adaptive feedback loops. Manage vector stores (Azure Cosmos DB, Azure SQL, FAISS) for

low-latency retrieval

. Design and maintain

FastAPI-based microservices

for inference, orchestration, and pipeline control. Collaborate with DevOps teams to automate deployments using

Azure Developer CLI (azd), Bicep, GitHub Actions

. Ensure enterprise-grade

security and governance

using Azure Key Vault, RBAC, private endpoints, and Purview policies. Monitor, evaluate, and optimize model performance using

Foundry Observability

and

Application Insights

.

Required Skills

Expert-level

Python

(LangChain, FastAPI, PyTorch/TensorFlow). Strong understanding of

RAG architecture

, embeddings, and semantic search principles. Hands-on experience with

Azure AI Search, Azure OpenAI, Azure AI Foundry

, and

Document Intelligence

. Proficiency with

Docker

, GitHub Codespaces, and container deployment workflows. Familiarity with hybrid retrieval and reranking techniques (BM25, neural rerankers). Strong foundation in NLP: tokenization, chunking, summarization, NER, sentiment analysis. Experience working with

vector databases

and embedding models. Knowledge of

Azure DevOps, Bicep, Terraform

, and CI/CD pipelines. Understanding of

security best practices

for AI systems (private endpoints, RBAC, secrets management).

Preferred Qualifications

Experience in

legal tech

, document automation, or enterprise document workflows. Familiarity with

Azure Machine Learning

for fine-tuning and MLOps. Exposure to

agentic/AI agent

applications and multi-turn workflow automation. Knowledge of

compliance frameworks

and secure AI deployment environments.
Job Types: Part-time, Freelance
Contract length: 12 months

Pay: ?30,000.00 - ?40,000.00 per month

Benefits:

Work from home
Experience:

total work: 6 years (Required)
Shift availability:

Night Shift (Required) Overnight Shift (Required)
Work Location: Remote