Azure AI Engineer

Job Description: Azure AI Engineer

Role Title:
Azure AI Engineer / Senior Azure AI/ML Engineer

Experience Level:
5+ Year

Role Overview

We are looking for an experienced

Azure AI Engineer

with 5+ years of hands-on experience in cloud, artificial intelligence, and machine learning architectures to design, build, and operationalize enterprise-grade AI and Generative AI solutions. In this role, you will leverage

Azure AI Foundry

,

Azure OpenAI Service

, and

Azure Machine Learning (Azure ML)

to build scalable RAG pipelines, deploy intelligent agents, and establish production MLOps/LLMOps workflows across enterprise workloads.

Key Responsibilities

1. Generative AI & LLM Solution Delivery

Architect and implement end-to-end GenAI applications utilizing

Azure OpenAI Service

(GPT-4o, reasoning models, and embedding models).

Build advanced Retrieval-Augmented Generation (RAG) architectures integrating

Azure AI Search

(vector, hybrid, and semantic re-ranking).

Develop, test, and orchestrate complex LLM workflows and multi-agent systems using frameworks like

Semantic Kernel

,

LangChain

,

LlamaIndex

, or

Prompt Flow

.

Fine-tune, evaluate, and benchmark foundation models on domain-specific datasets to meet accuracy, latency, and cost thresholds.

2. Model Lifecycle, Platform & Azure AI Foundry

Leverage

Azure AI Foundry

(formerly Azure AI Studio) to unify model exploration, prompt design, evaluation metrics, and model catalog deployments.

Build and manage machine learning training, tuning, and batch/real-time inference pipelines in

Azure Machine Learning (Azure ML)

.

Containerize and deploy models as scalable endpoints using Azure ML Managed Online Endpoints, Azure Container Apps, or Azure Kubernetes Service (AKS).

Manage model versioning, artifacts, metrics, and experimentation tracking using

MLflow

integrated with Azure ML.

3. LLMOps, Automation & Productionization

Build and maintain CI/CD pipelines via

Azure DevOps

or

GitHub Actions

for automated testing, evaluation gating, and blue-green deployment of AI models and RAG endpoints.

Embed automated LLM evaluation suites to systematically measure hallucination, groundedness, relevance, and toxicity prior to deployment.

Monitor runtime performance, inference latency, token usage, and compute costs using

Azure Monitor

,

Application Insights

, and custom telemetry dashboards.

4. Enterprise Security, Governance & Responsible AI

Enforce Responsible AI guidelines using

Azure AI Content Safety

, runtime guardrails, prompt injection defenses, and PII masking.

Secure AI infrastructure through Azure Virtual Networks (VNets), Private Endpoints, Azure Key Vault, Managed Identities, and strict Azure RBAC.

Required Technical Skills & Qualifications

Core Competencies:
Experience:
5+ years of overall technical experience, with at least 2–3 years focused on building, deploying, and operating AI/ML and GenAI systems on Microsoft Azure.

Azure AI & ML Stack:
Azure AI Foundry

(project hubs, prompt evaluation, model catalog).

Azure OpenAI Service

(API integration, quota management, fine-tuning).

Azure Machine Learning

(Compute Clusters, Environments, Pipelines, Endpoints, Datasets).

Azure AI Search

(Vector search, indexing, semantic ranker).

Programming & Frameworks:
Advanced proficiency in

Python

(Pandas, NumPy, AsyncIO).

Hands-on experience with LLM orchestration frameworks:
Semantic Kernel

,

LangChain

, or

LlamaIndex

.

Exposure to classical ML/DL libraries: scikit-learn, PyTorch, or Hugging Face.

Data & Storage:
Strong SQL skills, along with experience handling Azure Blob Storage, Azure Data Lake Storage (ADLS Gen2), and Cosmos DB.

DevOps & Infrastructure:
Docker containerization.

CI/CD automation via Azure DevOps or GitHub Actions.

Basic Infrastructure as Code (IaC) using Terraform or Bicep.

Preferred Qualifications

Certifications:
Microsoft Certified: Azure AI Engineer Associate (

AI-102

)

Microsoft Certified: Azure Data Scientist Associate (

DP-100)

We are proud of being IT Partners of choice of several medium and large

global organizations. Since our inception in 2014, we have grown by

addressing the evolving needs of our customers and contributing our best

towards their growth and success. We are a rapidly growing provider of IT

Solutions and Services offering a wide range of expertise to meet our

customers growing needs. We are focused on providing services around

Enterprise Solutions and Custom solutions.